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[Перевод] Учебник — всё, что вам нужно
Немного вызывающее название статьи отсылает к известной работе Внимание - всё, что вам нужно. На этот раз речь пойдет о качестве данных, на которых обучают LLM. Оказывается, качественный учебник (как концентрат знаний в любой сфере) в разы сокращает потребность и в памяти, и в мощности GPU, и в деньгах инвесторов...
Эта статья - о качестве данных при обучении/файнтюнинге LLM. Классическая работа о количественных данных позволит лучше понять, на что влияет качество датасета: Законы масштабирования нейронных языковых моделей
2 октября 2023
Аннотация
Мы представляем phi-1, новую большую языковую модель для генерации кода, которая значительно меньше по размеру по сравнению с конкурирующими моделями: phi-1 — это модель на основе архитектуры трансформера с 1,3 миллиардами параметров, обученная в течение 4 дней на 8 A100, с использованием выборки данных "качество-как-в-учебнике" из интернета (6 миллиардов токенов) а также синтетически сгенерированных с помощью GPT-3.5 учебников и упражнений (1 миллиард токенов). Несмотря на такой небольшой масштаб, phi-1 достигает точности pass@1 50,6% на HumanEval и 55,5% на MBPP. Модель также демонстрирует удивительные эмерджентные свойства по сравнению с phi-1-base, нашей моделью до этапа тонкой настройки (файнтюнинга) на наборе данных с упражнениями по программированию, и по сравнению с phi-1-small, меньшей моделью с 350 миллионами параметров, обученной по тому же конвейеру, что и phi-1, которая, однако, всё ещё достигает 45% на HumanEval.
1. Введение
Искусство обучения больших нейронных сетей показало невероятный прогресс за последнее десятилетие, особенно после открытия архитектуры трансформера [*], однако научные знания, стоящие за этим успехом, пока остаются ограниченными. Среди множества запутанных результатов появилось некое подобие порядка примерно в то же время, когда были представлены модели, основанные на трансформере. Было доказано, что производительность предсказуемо улучшается по мере увеличения либо объёма вычислений, либо размера сети [*], явление, которое теперь называют законами масштабирования [*]. Последующие исследования масштабирования в глубоком обучении взяли за основу эти законы масштабирования, и полученные результаты привели к резкому скачку в производительности. В этой работе, следуя по стопам Eldan и Li [*], мы исследуем улучшения, которые можно получить вдоль другой оси: качество данных.
Давно известно, что данные более высокого качества приводят к лучшим результатам, например, очистка данных является важной частью создания современных наборов данных, это также может дать другие дополнительные преимущества, такие как несколько меньшие наборы данных или возможность делать больше проходов по данным. Недавняя работа Eldan и Li над TinyStories (высококачественным набором данных, синтетически сгенерированным для обучения нейронных сетей английскому языку) показала, что эффект высококачественных данных выходит далеко за пределы этого: улучшение качества данных может кардинально изменить форму законов масштабирования, потенциально позволяя достичь производительности больших моделей с гораздо более скромными затратами на обучение модели.
В этой работе мы выходим за рамки первоначального исследования Eldan и Li, чтобы показать, что высококачественные данные могут даже улучшить SOTA больших языковых моделей (LLM), при этом значительно сокращая размер набора данных и объём вычислений для обучения. Важно, что меньшие модели, требующие меньше обучения, могут значительно снизить экологические издержки от LLM.
Мы сосредоточим внимание на LLM, обученных для генерации кода, и, в частности, на написании простых функций на Python, используя их строки документации (docstrings), см. [*]. Бенчмарк, предложенный в последней работе, HumanEval, широко используется для сравнения производительности LLM в генерации кода. Мы демонстрируем мощь высококачественных данных, которые нарушают существующие законы масштабирования, обучая модель с 1,3 миллиардами параметров, которую мы называем phi-1, примерно на 8 проходах по 7 миллиардам токенов (всего чуть более 50 миллиардов токенов) с последующей тонкой настройкой (файнтюнингом) на менее чем 200 миллионах токенов.
Грубо говоря, мы предварительно обучаем на данных с качеством "как в учебнике", как синтетически сгенерированных (с помощью GPT-3.5), так и отфильтрованных из веб-источников, и проводим файнтюнинг на данных, похожих на упражнения из учебника.
Несмотря на то, что модель на несколько порядков меньше конкурирующих моделей как по размеру набора данных, так и по размеру модели (см. Таблицу 1), мы достигаем точности 50,6% pass@1 на HumanEval и 55,5% pass@1 на MBPP (Mostly Basic Python Programs), что является одним из лучших самостоятельно заявленных результатов с использованием только одной генерации LLM.
Таблица 1: Мы используем данные отчетов, если они доступны. Несмотря на то, что phi-1 обучалась на значительно меньшем объеме данных, она превосходит конкурирующие модели по метрикам HumanEval и MBPP, за исключением модели GPT-4 (также WizardCoder показывает лучший результат на HumanEval, но хуже на MBPP).
Дата | Модель | Размер (параметры) модели | Размер датасета (токенов) | HumanEval | MBPP |
Jul 21 | Codex-300M [CTJ + 21] | 300M | 100B | 13.2% | N.A. |
Jun 23 | phi-1 | 1.3B | 7B | 50.6% | 55.5% |
CodeGen-Mono: [NPH + 23], StarCoder-Prompted: [LAZ + 23], InstructCodeT5+: [WLG + 23]
В Разделе 2 мы приводим некоторые детали нашего процесса обучения и обсуждаем доказательства важности нашего процесса отбора данных для достижения этого результата. Более того, несмотря на обучение на значительно меньшем количестве токенов по сравнению с существующими моделями, phi-1 всё же демонстрирует эмерджентные свойства.
Эмерджентность — это явление, когда в системе возникают новые свойства или поведение, которые не характерны для отдельных её компонентов. Т.е. это проявления феномена, когда целое больше, чем сумма его частей - прим. переводчика.
В Разделе 3 мы обсудим эти эмерджентные свойства и, в частности, подтвердим гипотезу о том, что количество параметров играет ключевую роль в эмерджентности (см., например, [WTB22]), сравнивая вывод модели phi-1 с выводом phi-1-small, модели, обученной по тому же конвейеру, но только с 350 миллионами параметров. Методология, используемая в этом разделе, напоминает работу Sparks of AGI, в которой утверждается, что необходимо отойти от статических бенчмарков для тестирования производительности LLM.
Наконец, в Разделе 4 мы обсудим альтернативные бенчмарки для оценки модели, а в Разделе 5 изучим возможное загрязнение наших обучающих данных в отношении HumanEval. Мы выкладываем модель для использования и оценки широким сообществом, но опускаем некоторые детали синтетической генерации данных по причинам наличия прав собственности.
Другие работы по темеНаша работа является частью недавней программы использования LLM для синтеза программного кода, дополнительные ссылки на которую см. в [CTJ+21, NPH+22]. Наш подход также является частью тенденции использования существующих LLM для синтеза данных для обучения новых поколений LLM, [WKM+22, TGZ+23, MMJ+23, LGK+23, JWJ+23]. В настоящее время ведутся споры о том, что возможно такое “рекурсивное обучение” приведет к деградации моделей [SZ+23, GUESS+23], противоположную точку зрения смотрите в [MMJ+23].
Обратите внимание, что в этой статье мы фокусируемся на узкой задаче, аналогично [JWJ +23], при которой достижение лучшей производительности, чем у исходной LLM, кажется реалистичным (что и доказывается статье).
2. Детали обучения и важность высококачественных данных
Рисунок 2.1: Точность Pass@1 (%) на HumanEval. Группировка столбчатых диаграмм соответствует: 1)обычным параметрам масштабирования, 2)увеличению времени вычислений (больше проходов по данным, здесь от 26 млрд токенов до 76 млрд), 3)увеличению количества параметров модели (здесь от 350 млн до 1.3 млрд). Каждый столбец внутри группы соответствует различным обучающим наборам данных: (A) Первый (оранжевый) столбец представляет производительность моделей, обученных на стандартном наборе данных с Python-файлами из The Stack (плюс StackOverflow для модели с 1.3 млрд параметров); (B) Второй (светло-синий) столбец представляет производительность моделей, обученных на нашем новом наборе данных CodeTextbook; (C) Наконец, третий (темно-синий) столбец соответствует моделям второй колонки, дообученным на нашем новом наборе данных CodeExercises.
Для моделей с 1.3 млрд параметров phi-1 и phi-1-base являются контрольными точками после обучения на 51 млрд токенов (770 GPU-часов), а модель The Stack+ была обучена на 76 млрд токенов и 1090 GPU-часов. Мы подчеркиваем, что даже без какого-либо дообучения наша модель phi-1-base, обученная на наборе данных CodeTextbook, достигает 29% производительности на HumanEval при всего 1.3 млрд параметров. Предыдущая самая маленькая модель, достигшая около 30% производительности на HumanEval, это Replit-Finetuned с 2.7 млрд параметров, которая была обучена на объеме токенов в 100 раз больше, чем наша [Rep23]. Кроме того, дообучение на нашем наборе данных CodeExercises для получения phi-1 не только дало нам максимальную производительность 51% на HumanEval, но и раскрыло дополнительные неожиданные возможности кодирования (см. Раздел 3).
Как намекает название статьи, ключевым ингредиентом нашей модели являются данные обучения "качества как в учебнике". В отличие от предыдущих работ, которые использовали стандартные источники текстовых данных для генерации кода, такие как The Stack (содержащий исходный код из репозиториев с разрешающими лицензиями) и другие веб-наборы данных (например, StackOverflow и CodeContest [*]), мы утверждаем, что эти источники не оптимальны для обучения модели алгоритмическому мышлению и планированию. С другой стороны, архитектура нашей модели и методы обучения довольно традиционны (Раздел 2.3), поэтому этот раздел мы посвящаем в основном объяснению того, как мы отбирали наши данные.
Стандартные наборы данных для кода [*, *] представляют собой большой и разнообразный корпус, охватывающий широкий спектр тем и случаев использования. Однако, основываясь на ручном анализе случайных выборок, мы можем сказать, что многие из этих фрагментов кода далеко не очень полезны для изучения основ программирования и страдают от нескольких недостатков:
Многие примеры не самодостаточны, то есть они зависят от других модулей или файлов, внешних по отношению к фрагменту, что делает их трудными для понимания без дополнительного контекста.
Типичные примеры не содержат значимых вычислений, а скорее состоят из тривиального или шаблонного кода, такого как определение констант, установка параметров или настройка элементов графического интерфейса.
Примеры, содержащие алгоритмическую логику, часто скрыты внутри сложных или плохо документированных функций, что затрудняет их понимание или изучение.
Примеры смещены в сторону определённых тем или случаев использования, что приводит к несбалансированному распределению концепций и навыков программирования в наборе данных.
Можно представить, насколько неэффективной и полной разочарований стала бы попытка человека освоить навыки программирования по таким наборам данных, так как ему пришлось бы иметь дело с большим количеством шума, неоднозначности и неполноты данных.
Мы предполагаем, что эти проблемы также влияют на производительность языковых моделей, поскольку они снижают качество и количество сигналов, которые связывают естественный язык с кодом. Мы предполагаем, что языковые модели выиграют от обучающего набора данных, который обладает теми же качествами, что и хороший "учебник": он должен быть ясным, самодостаточным, поучительным и сбалансированным.
В этой работе мы напрямую решаем эту проблему и показываем, что целенаправленно отбирая и генерируя высококачественные данные можно достичь современных результатов в задачах генерации кода с гораздо меньшим размером модели и меньшими вычислительными затратами, чем существующие подходы. Наше обучение основывается на трёх основных наборах данных:
Отфильтрованный набор данных "код-язык", который представляет собой подмножество The Stack и StackOverflow, полученное с использованием классификатора на основе языковой модели (состоящий из около 6 миллиардов токенов).
Синтетический датасет "учебников", состоящий из менее чем 1 миллиарда токенов учебников по Python, сгенерированных GPT-3.5.
Небольшой датасет "упражнения", состоящий из ~180 миллионов токенов упражнений и решений на Python.
Мы подробно описываем эти наборы данных в следующих подразделах. В совокупности вышеуказанные наборы данных содержат менее 7 миллиардов токенов. Мы называем "CodeTextbook" комбинацию отфильтрованного набора данных "код-язык" и синтетического набора данных "учебников" и используем его на этапе предварительного обучения для получения нашей базовой модели phi-1-base — эта модель уже достигает конкурентоспособной производительности на HumanEval в 29%.
Затем мы используем набор данных "упражнения" из 180 миллионов токенов, называемый "CodeExercises", для файнтюнинга нашей модели phi-1-base для создания phi-1. Несмотря на небольшой размер набора данных "CodeExercises", файнтюнинг с этим набором данных имеет решающее значение не только для значительного улучшения генерации простых функций на Python, как показано на Рисунке 2.1, но и для разблокировки многих интересных эмерджентных возможностей в нашей модели phi-1, которые не наблюдаются в phi-1-base (см. Раздел 3).
2.1 Фильтрация существующих наборов данных с использованием классификатора на основе трансформера
Мы начинаем с общедоступных наборов данных на Python: используем подмножество Python из дедуплицированной версии The Stack и StackOverflow, которые вместе содержат более 35 миллионов файлов/примеров, всего более 35 миллиардов токенов.
Мы аннотируем качество небольшого подмножества этих файлов (около 100 тысяч примеров) с помощью GPT-4: для каждого фрагмента кода у GPT-4 запрашивается: "определить образовательную ценность для студента, цель которого — изучить основные концепции программирования".
Затем мы используем этот аннотированный набор данных для обучения классификатора на основе случайного леса, который предсказывает качество файла/примера, используя выдачу из предварительно обученной codegen-модели в виде соответствующих признаков. Мы отмечаем, что, в отличие от GPT-3.5, который мы активно используем для генерации синтетического контента (обсуждается ниже), мы используем GPT-4 минимально только для аннотирования качества небольшого подмножества примеров из The Stack и StackOverflow. Таким образом, мы рассматриваем использование GPT-4 как способ избежать утомительных усилий по ручному аннотированию [*].
Образовательная ценность, определенная фильтром / Высокая ценность (слева) / Низкая ценность (справа)
Код выше в формате python:# Высокая ценность
import torch
import torch.nn.functional as F
def normalize(x, axis=-1):
"""Performs L2-Norm."""
num = x
denom = torch.norm(x, 2, axis, keepdim=True)
.expand_as(x) + 1e-12
return num / denom
def euclidean_dist(x, y):
"""Computes Euclidean distance."""
m, n = x.size(0), y.size(0)
xx = torch.pow(x, 2).sum(1, keepdim=True).
expand(m, n)
yy = torch.pow(x, 2).sum(1, keepdim=True).
expand(m, m).t()
dist = xx + yy - 2 * torch.matmul(x, y.t())
dist = dist.clamp(min=1e-12).sqrt()
return dist
def cosine_dist(x, y):
"""Computes Cosine Distance."""
x = F.normalize(x, dim=1)
y = F.normalize(y, dim=1)
dist = 2 - 2 * torch.mm(x, y.t())
return dist# Низкая ценность
import re
import typing
...
class Default(object):
def __init__(self, vim: Nvim) -> None:
self._vim = vim
self._denite: typing.Optional[SyncParent] = None
self._selected_candidates: typing.List[int] = []
self._candidates: Candidates = []
self._cursor = 0
self._entire_len = 0
self._result: typing.List[typing.Any] = []
self._context: UserContext = {}
self._bufnr = -1
self._winid = -1
self._winrestcmd = ''
self._initialized = False
self._winheight = 0
self._winwidth = 0
self._winminheight = -1
self._is_multi = False
self._is_async = False
self._matched_pattern = ''
...Наш метод фильтрации значительно повышает производительность модели даже без использования синтетических наборов данных, описанных ниже: для моделей с 350 миллионами параметров, обученных на неотфильтрованном Stack (дедуплицированный Python) и StackOverflow, производительность на HumanEval достигает предела на уровне 12,19%, даже после 96 тысяч шагов обучения (~200 млрд токенов). При этом обучение на отфильтрованном подмножестве данных даёт результат 17,68% на HumanEval уже после 36 тысяч шагов. Мы дополнительно улучшили этот показатель до 20,12% (см. рисунок 2.1), обучая модель на комбинации отфильтрованного набора данных и синтетического набора данных из учебников, описанного ниже.
2.2 Создание синтетических наборов данных с "качеством учебника"
Одной из основных проблем при создании высококачественного набора данных для генерации кода является обеспечение того, чтобы примеры были разнообразными и не повторялись.
Под разнообразием мы понимаем, что примеры должны охватывать широкий спектр концепций, навыков и сценариев программирования, а также варьироваться по уровню сложности, стилю и структуре. Разнообразие важно по нескольким причинам: оно знакомит языковую модель с различными способами выражения и решения задач в коде, снижает риск переобучения или запоминания конкретных шаблонов или решений, а также повышает возможности обобщения и устойчивость модели к новым или незнакомым задачам. Однако достижение разнообразия — нетривиальная задача, особенно при использовании синтетических данных, сгенерированных другой языковой моделью. Простое указание модели создать учебник по программированию или набор упражнений, даже с некоторыми вариациями в инструкциях или параметрах, скорее всего, приведёт к созданию однородного и избыточного набора данных, где одни и те же концепции и решения повторяются с незначительными изменениями. Это происходит потому, что языковые модели склонны следовать наиболее вероятным или распространённым путям, исходя из их обучающих данных и априорных знаний, и у них нет стимула или творческого подхода для исследования альтернативных или новых способов генерации кода. Поэтому необходимо найти правильный "трюк", который заставит языковую модель быть более креативной и разнообразной в своих выводах, сохраняя при этом качество и связность примеров.
Вдохновлённые работой [*], в которой путём включения случайного подмножества слов из фиксированного словаря в запрос и требования их комбинирования в сгенерированном тексте был создан разнообразный набор коротких историй, мы ищем способы внедрения случайности в запрос таким образом, чтобы это способствовало созданию набора данных с высоким разнообразием.
Синтетический набор данных "учебников"
Этот набор данных состоит из менее чем 1 миллиарда токенов учебников по Python, сгенерированных GPT-3.5, и предназначен для предоставления высококачественного источника текста с естественным языком, перемежающегося соответствующими фрагментами кода. Мы также ориентировали содержание этих учебников на темы, которые способствуют развитию логического мышления и базовых алгоритмических навыков. Разнообразие достигается за счёт наложения ограничений на темы и целевую аудиторию генерируемого учебника. Вот пример текста из синтетического учебника:
Для начала давайте определим, что такое сингулярные и несингулярные матрицы. Матрица называется сингулярной, если её определитель равен нулю. С другой стороны, матрица называется несингулярной, если её определитель не равен нулю. Теперь давайте рассмотрим эти концепции на примерах.
Пример 1: Рассмотрим матрицу
A = np.array([[1, 2], [2, 4]]). Мы можем проверить, является ли эта матрица сингулярной или несингулярной, используя функцию определителя. Мы можем определить функцию на Python,is_singular(A), которая возвращаетTrue, если определитель A равен нулю, иFalseв противном случае.
import numpy as np
def is_singular(A):
det = np.linalg.det(A)
if det == 0:
return True
else:
return False
A = np.array([[1, 2], [2, 4]])
print(is_singular(A)) # TrueНабор данных "CodeExercises"
Это небольшой синтетический набор данных "упражнения", состоящий из менее чем 180 миллионов токенов упражнений и решений на Python. Каждое упражнение представляет собой строку документации функции, которую необходимо завершить. Цель этого набора данных — настроить модель на выполнение задач по завершению функций на основе инструкций на естественном языке. Этот набор данных также был сгенерирован GPT-3.5, где основным способом достижения разнообразия является ограничение на имена функций. Для этого набора данных мы проводим явную деконтаминацию и альтернативные оценки в следующих разделах, чтобы убедиться, что задачи, похожие на те, что представлены в бенчмарке HumanEval, не встречаются во время файнтюнинга. Следующий фрагмент иллюстрирует синтетически сгенерированное упражнение:
def valid_guessing_letters(word: str, guesses: List[str]) -> List[str]:
"""
Returns a list of valid guessing letters, which are letters that have not been guessed yet and
are present in the word.
Parameters:
word (str): The word to guess.
guesses (List[str]): A list of letters that have already been guessed.
Returns:
List[str]: A list of valid guessing letters.
"""
valid_letters = []
for letter in word:
if letter not in guesses and letter not in valid_letters:
valid_letters.append(letter)
return valid_letters2.3. Архитектура модели и обучение
Мы использовали трансформер с декодером [*], использующий реализацию FlashAttention для многоголового внимания (MHA) [*]. Также мы применили MHA и слои MLP в параллельной конфигурации, следуя недавним моделям, таким как CodeGen [*], PaLM [*] и GPT-NeoX [*].
Архитектура нашей модели phi-1 с 1.3 миллиардами параметров состоит из 24 слоев, скрытой размерности 2048, внутренней размерности MLP 8192 и 32 голов внимания размерностью 64 каждая.
Меньшая модель phi-1-small с 350 миллионами параметров имеет 20 слоев, скрытую размерность 1024, внутреннюю размерность MLP 4096 и 16 голов внимания размерностью 64 каждая.
Мы также использовали вращающийся позиционный эмбеддинг (rotary position embedding) [*] с размерностью вращения 32. Эти архитектурные решения были заимствованы из [*]. Мы использовали тот же токенизатор, что и в codegen-350M-mono [*]. Помимо FlashAttention, наши модели не используют другие техники, такие как Fill-In-the-Middle (FIM) [*] или Multi-Query-Attention (MQA) [*], которые могли бы дополнительно повысить производительность и эффективность [*].
Для предобучения и дообучения (файнтюнинга) мы объединили соответствующие наборы данных в одномерный массив, используя токен «⟨∣endoftext∣⟩» для разделения файлов. Мы обучали наши модели на последовательностях длиной 2048, взятых из нашего массива данных с функцией потерь прогнозирования следующего токена. Обучение проводилось с использованием fp16, оптимизатора AdamW, линейного графика обучения с разогревом и затуханием, а также внимания и остаточного dropout на уровне 0,1. Обучение выполнялось на 8 GPU Nvidia A100 с использованием deepspeed. Наша базовая предобученная модель phi-1-base была получена менее чем за 4 дня обучения. Дообучение (файнтюнинг) для получения phi-1 заняло дополнительные 7 часов на том же оборудовании.
Предобучение (Pretraining)
phi-1-base был обучен на датасете CodeTextbook (отфильтрованный корпус кода и синтетические учебники). Мы использовали эффективный размер батча 1024 (включая параллелизм данных и накопление градиентов), максимальную скорость обучения 1e-3 с разогревом в течение 750 шагов и коэффициентом регуляризации весов 0,1 всего за 36,000 шагов. Мы использовали контрольную точку на 24,000 шаге в качестве нашей phi-1-base — это эквивалентно примерно 8 эпохам на нашем наборе данных CodeTextbook, что составляет чуть более 50 миллиардов тренировочных токенов. Несмотря на малый размер и вычислительные ресурсы, эта модель уже достигает точности 29% на HumanEval.
Файнтюнинг
phi-1 получена путем файнтюнинга phi-1-base на наборе данных CodeExercises. Для файнтюнинга мы использовали ту же настройку, что и для предобучения, но с другими гиперпараметрами: эффективный размер батча 256, максимальная скорость обучения 1e-4 с разогревом в течение 50 шагов и коэффициентом регуляризации весов 0.01. Мы обучали модель в течение общего количества шагов 6000 и выбирали лучшую контрольную точку (сохраняемую каждые 1000 шагов).
3. Скачок возможностей модели после файнтюнинга на наборе CodeExercises
На Рисунке 2.1 показано, что наибольшее улучшение в результатах на HumanEval было достигнуто благодаря файнтюнингу на небольшом наборе данных CodeExercises (<200 млн токенов). CodeExercises состоит исключительно из коротких задач на Python с использованием только базовых библиотек. В этом разделе мы продемонстрируем интересный факт: модель после дообучения показывает значительное улучшение также в выполнении задач, которые не представлены в наборе данных для дообучения. В том числе управление сложными алгоритмическими задачами и использование внешних библиотек.
Это позволяет предположить, что процесс файнтюнинга мог помочь модели реорганизовать и закрепить знания, полученные во время предварительного обучения, даже если такие знания явно не присутствуют в нашем наборе данных CodeExercises. В этом разделе мы сосредоточимся на качественном сравнении возможностей нашей дообученной модели phi-1 и её базовой модели phi-1-base с 1,3 млрд параметров.
3.1 Файнтюнинг улучшает понимание модели
Используя простую функцию Python, которую мы создали самостоятельно, мы наблюдаем, что модель демонстрирует значительно более высокий уровень понимания и соответствия инструкциям после файнтюнинга. В частности, мы видим, что phi-1-base испытывает трудности с логическими связями в запросах, в то время как phi-1 может интерпретировать вопрос и сгенерировать правильный ответ. В этом примере даже наша 350-миллионная модель phi-1-small показывает некоторый уровень понимания проблемы, хотя итоговое решение оказывается неверным. Мы наблюдаем такие тенденции последовательно в процессе наших взаимодействий с моделью, см. другой пример в Приложении A.
Промпт: Алиса, Боб и Чарльз играют в игру. Сначала Алиса выбирает случайное число от 333 до 678, затем Боб выбирает число от числа Алисы до 888, а затем Чарльз выбирает число от 123 до числа Боба. Алиса получает одно очко, если разность числа Алисы и числа Чарльза делится на целую часть квадратного корня из числа Боба. В противном случае Боб получает одно очко. Смоделируйте очки Алисы и Боба за 30 итераций.
Код предыдущего примера:# phi-1
points = [0, 0]
for i in range(30):
alice_num = random.randint(333, 678)
bob_num = random.randint(alice_num, 888)
charles_num = random.randint(123, bob_num)
if (alice_num - charles_num) % int(bob_num ** 0.5) == 0:
points[0] += 1
else:
points[1] += 1
return f"Alice: {points[0]}, Bob: {points[1]}"# phi-1-base
self.points = 0
self.alice = 333
self.bob = 678
self.charles = 888
self.bob_points = 0
self.alice_points = 0
self.iterations = 30
self.alice_turn = True
self.bob_turn = True
self.alice_turn_points = 0
self.bob_turn_points = 0
self.alice_turn_points_history = []
self.bob_turn_points_history = []
self.alice_turn_points_history.append(self.alice_points)
self.bob_turn_points_history.append(self.bob_points)# phi-1-small
indices = []
import random
alice_points = 0
bob_points = 0
for i in range(30):
alice_num = random.randint(333, 678)
bob_num = random.randint(123, bob_num)
if (alice_num - bob_num) % math.floor(math.sqrt(bob_num)) == 0:
alice_points += 1
if (i % 2) == 0:
bob_points += 1
print(f"Alice gets {alice_points} points, while Bob gets {bob_points} points.")3.2. Файнтюнинг улучшает способность модели использовать внешние библиотеки
Мы продемонстрируем, что дообучение на наборе CodeExercises неожиданно улучшает способность модели использовать внешние библиотеки, такие как Pygame и Tkinter, несмотря на то, что наши упражнения не содержат этих библиотек. Это позволяет предположить, что наше дообучение не только улучшает выполнение целевых задач, но также облегчает извлечение знаний для несвязанных задач, полученных в ходе предварительного обучения. Для справки, на Рисунке 3.1 показано распределение импортов пакетов в нашем наборе данных CodeExercises.
Рисунок 3.1: Количество импортов среди ∼880 тыс. упражнений в CodeExercises (мы игнорируем библиотеки, импортированные менее 10 раз). Код для построения графика был сгенерирован моделью phi-1 по запросу:
«У меня есть словарь, сначала отсортируйте его по значениям от наибольшего к наименьшему. Затем постройте столбчатую диаграмму с помощью pyplot. Сначала установите размер шрифта 7, затем поверните метки на оси X на 90 градусов. Ось X — это ключи, ось Y — значения словаря. Используйте логарифмическую шкалу для оси Y. Кроме того, установите метку оси Y как «Log Number of Times», а метку оси X как «Imports». Установите dpi на 1000.»
«У меня есть словарь, сначала отсортируйте его по значениям от наибольшего к наименьшему. Затем постройте столбчатую диаграмму с помощью pyplot. Сначала установите размер шрифта 7, затем поверните метки на оси X на 90 градусов. Ось X — это ключи, ось Y — значения словаря. Используйте логарифмическую шкалу для оси Y. Кроме того, установите метку оси Y как «Log Number of Times», а метку оси X как «Imports». Установите dpi на 1000.»
Пример с PyGame
Мы начинаем с запроса к модели, в котором просим сгенерировать код для перемещения мяча в PyGame:
Промпт: Напишите код на PyGame. Есть мяч. На каждой итерации: 1. Координата X мяча увеличивается на случайное целое число в диапазоне (-10, 10). 2. Координата Y мяча увеличивается на случайное целое число в диапазоне (-20, 20). Координата X мяча должна оставаться в пределах от 0 до 400, а координата Y — в пределах от 0 до 600. Когда пользователь нажимает пробел, установите координату X мяча на 200, а координату Y — на 400.
Код примеров:# phi-1
...
screen = pygame.display.set_mode((400, 600))
x, y = 0, 0
while True:
for event in pygame.event.get():
...
elif event.type == pygame.KEYDOWN:
if event.key == pygame.K_SPACE:
x = 200
y = 400
x += random.randint(-10, 10)
y += random.randint(-20, 20)
if x < 0:
x = 0
elif x > 400:
x = 400
if y < 0:
y = 0
elif y > 600:
y = 600
screen.fill((255, 255, 255))
pygame.draw.circle(screen, (255, 0, 0), (x, y), 10)
pygame.display.update()# phi-1-base
...
ball_x = random.randint(-10, 10)
ball_y = random.randint(-20, 20)
ball_vx = random.randint(-5, 5)
ball_vy = random.randint(-5, 5)
...
screen = pygame.display.set_mode((800, 600))
...
while not done:
for event in pygame.event.get():
...
elif event.type == pygame.KEYDOWN:
if event.key == pygame.K_SPACE:
ball_x = 200
ball_y = 400
ball_x += ball_vx
ball_y += ball_vy
ball_vx += ball
pygame.display.flip()# phi-1-small
...
x, y = 0, 0
dx, dy = random.randint(-10, 10), random.randint(-20, 20)
while True:
screen.fill((0, 0, 0))
pygame.draw.rect(screen, (255, 255, 255), (x, y, 400, 600))
pygame.display.update()
x += dx
y += dy
if x + dx > 400:
dx = -dx
elif x + dx < 0:
dx = dx
if y + dy > 600:
dy = -dy
elif y + dy < 0:
dy = dy
pygame.time.wait(50)Приведенный выше фрагмент кода показывает основной цикл простой программы на PyGame, в которой мяч отскакивает на экране. Модель phi-1 корректно применяет функции PyGame для обновления и отрисовки мяча, следуя инструкциям из запроса. Модели phi-1-base и phi-1-small генерируют вызовы функций, которые синтаксически правильны, но семантически не соответствуют задаче. Мы видим, что phi-1-base демонстрирует некоторую способность использовать соответствующие вызовы API, но не может следовать логике задачи, в то время как phi-1-small после дообучения понимает логику, но не обладает достаточной емкостью для изучения правильных вызовов функций.
Пример с TKinter
Наш второй пример — это приложение на TKinter, в котором мы просим модель обновлять текстовое поле в зависимости от нажатия кнопок.
Промпт: Напиши приложение на tkinter. В верхней части находится текстовое поле, внизу — кнопка "Submit", а рядом с ней — кнопка "Recover". При нажатии на кнопку "Submit" получи текст из текстового поля и сохрани его в глобальную строку s. Если текст содержит слово "pew", обновите текст в текстовом поле на "pewpewpew?". В противном случае добавьте в конец текста "no pew...". При нажатии на кнопку "Recover" замените текст в текстовом поле на значение строки s.
Код выше:# phi-1
...
global s
s = ""
def submit():
global s
text = textfield.get()
if "pew" in text:
textfield.delete(0, tk.END)
textfield.insert(0, "pewpewpew...")
else:
textfield.delete(0, tk.END)
textfield.insert(0, text + "no pew...")
s = text
def recover():
global s
textfield.delete(0, tk.END)
textfield.insert(0, s)
textfield = tk.Entry(root)
textfield.pack()
submit_button = tk.Button(root, text="Submit", command=submit)
submit_button.pack()
recover_button = tk.Button(root, text="Recover", command=recover)
recover_button.pack()
root.mainloop()# phi-1-base
global s
s = s.replace("pew", "pewpewpew")
if "pew" in s:
s = s.replace("pew", "pewpewpew")
else:
s = s + "no pew..."
text.delete(0.0, END)
text.insert(0.0, s)
def main():
global s
s = "pewpewpew"
text.delete(0.0, END)
text.insert(0.0, s)
text.tag_add("button", "<Button-1>", "<Button-3>")
text.tag_add("button", "<Button-2>", "<Button-4>")
# The model keeps adding buttons from here# phi-1-small
import tkinter as tk
root = tk.Tk()
global s
text = ""
while True:
event, values = tk.popup()
if event == "submit":
text += values.split()[0] + " "
elif event == "textfield":
s += values.split()[0] + " "
elif event == "submit-button-text":
text = values.split()[0] + " "
elif event == "text-button-text":
s = text
if "pew" in text:
text = text.replace("pew", "pewpewpew")
if "no pew" in text:
break
tk.destroy()Результаты выполнения трех моделей демонстрируют значительный разрыв в их понимании запросов. И phi-1-base, и phi-1-small не смогли использовать правильные API Tkinter и создали бессмысленные вызовы функций. С другой стороны, phi-1 корректно реализовала графический интерфейс и все функции (за исключением небольшой ошибки в копировании строки "pewpewpew?"). В Приложении A мы приводим два дополнительных примера для pytorch и pyplot.
Пример в режиме чата.
Наконец, мы покажем, что phi-1 обладает лучшими способностями к ведению диалога по сравнению с phi-1-base, несмотря на то, что данные для чата присутствовали только на этапе предварительного обучения, а не файнтюнинга.
Промпт: Студент: У меня есть график на Python pyplot, я хочу увеличить его разрешение и повернуть. Что мне делать? Ассистент:
Ответ phi-1:
Установите параметр
dpiна желаемое разрешение (например, 300 для 300 DPI).Используйте функцию
rotateиз модуляmatplotlib.pyplot, чтобы повернуть график на 90 градусов по часовой стрелке.
Пример:
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
ax.plot([1, 2, 3], [4, 5, 6])
# Установите разрешение на 300 DPI
ax.set_dpi(300)
# Поверните график на 90 градусов по часовой стрелке
ax.rotate(90) Ответ phi-1-base:
Вы можете использовать функцию setp() для установки разрешения и функцию set_rotation() для поворота графика. <|endoftext|>
Ответ phi-1-small:
Я — график на Python pyplot, и я хочу увеличить его разрешение и повернуть. Что мне делать?
ВТОРОЙ:
Я — график на Python pyplot, и я хочу увеличить его разрешение и повернуть. Что мне делать?
ТРЕТИЙ:...
4. Оценка на нестандартных задачах с использованием LLM-оценки (LLM grading)
Одной из потенциальных проблем, связанных с удивительно высокой производительностью модели phi-1 на HumanEval (см. Таблицу 1 и Рисунок 2.1), может быть запоминание данных из-за возможного загрязнения синтетического набора данных CodeExercises. Мы изучим это потенциальное загрязнение напрямую в Разделе 5, а в этом разделе рассматрим эту проблему с помощью новой оценки, которая была разработана достаточно нестандартно, чтобы её появление в нашем обучающем наборе данных было маловероятно.
Чтобы минимизировать предвзятость и утечку данных, новые задачи для оценки были созданы специальной командой, которая не имела доступа к набору данных CodeExercises или финальной модели. Они создали 50 новых задач в том же формате, что и HumanEval, с инструкциями разработать задачи, которые вряд ли появятся в реальных базах кода или в качестве учебных упражнений. Вот пример такой задачи:
""" Эта функция принимает два списка целых чисел, сортирует каждый из них по возрастанию, объединяет их, возводит в квадрат элементы на четных индексах, фильтрует элементы, меньшие чем my_threshold, и затем удаляет дубликаты. Результирующий список возвращается. """
Одной из сложностей оценки языковых моделей на задачах по программированию является то, что вывод модели часто бинарный: либо код проходит все unit-тесты, либо не проходит. Однако это не отражает нюансов производительности модели, так как она может сгенерировать код, который почти правильный, но содержит небольшую ошибку, или код, который полностью неверен, но случайно проходит некоторые тесты. Более информативным способом оценки навыков модели может быть сравнение её вывода с правильным решением и выставление оценки на основе того, насколько хорошо оно соответствует ожидаемой логике. Это похоже на то, как люди оцениваются на собеседованиях по программированию, где интервьюер не только запускает код, но и анализирует рассуждения и качество решения.
Для оценки решений мы используем подход, при котором GPT-4 выступает в роли оценщика (как, например, в [*]). Этот подход имеет два преимущества:
(1) используя GPT-4 в качестве оценщика, мы можем использовать его знания и генеративные способности для получения более детального и осмысленного сигнала о способностях модели к программированию, и
(2) это устраняет необходимость в тестах.
Наш запрос инструктирует LLM оценить решение студента сначала в краткой вербальной оценке, а затем выставить оценку от 0 до 10.
Таблица 2: Оценки понимания (Understanding scores) на 50 новых нестандартных задачах по программированию, выставленные с использованием LLM.
Модель | Размер | Токенов обучения | Оценка | Human-Eval |
CodeGen-Mono-350M [NPH+23] CodeGen-Mono-16.1B [NPH+23] Replit [Rep23] StarCoder [LAZ+23]350M | 350M 16.1B 2.7B 15.5B | 577B 577B 525B 1T | 19% 38% 37% 51% | 13% 29% 22% 34% |
phi-1-base phi-1-small phi-1 | 1.3B 350M 1.3B | 7B 7B 7B | 37% 45% 52% | 29% 45% 51% |
См. Таблицу 2 для наших результатов с phi-1 и конкурирующими моделями. Оценки на наших новых нестандартных задачах дают тот же рейтинг, что и HumanEval (см. Таблицу 1). phi-1 снова демонстрирует результат значительно выше, чем StarCoder, как и на HumanEval. Учитывая, что новые задачи не могли загрязнить обучающие данные и, более того, были разработаны так, чтобы находиться за пределами распределения обучающих данных, эти результаты значительно повышают нашу уверенность в достоверности производительности phi-1.
5. Удаление (очистка) данных для объективной оценки производительности
На Рисунке 2.1 мы видим, что обучение на наборе данных CodeExercises приводит к значительному улучшению производительности модели на бенчмарке HumanEval. Чтобы исследовать это улучшение, мы предлагаем "очистить" набор данных CodeExercises, удалив файлы, которые "похожи" на те, что содержатся в HumanEval. Этот процесс можно рассматривать как "строгую форму" дезактивации данных. Затем мы повторно обучаем нашу модель на таких очищенных данных и всё ещё наблюдаем высокую производительность на HumanEval. В частности, даже после агрессивного удаления более 40% набора данных CodeExercises (это включает удаление файлов, которые лишь отдалённо похожи на HumanEval, см. Приложение C), повторно обученная модель phi-1 всё равно превосходит StarCoder.
Мы считаем, что такой эксперимент с удалением данных является справедливым способом оценки производительности и более информативным, чем стандартные исследования "загрязнения" в литературе, которые обычно основаны на измерении пересечения между обучающими и тестовыми данными (например, Раздел 4.8 в [*]). Для полноты картины мы начинаем этот раздел с проведения стандартного эксперимента на загрязнение, который показывает, что CodeExercises не загрязнён данными из HumanEval в этом стандартном смысле.
5.1 Перекрытие N-грамм
N-граммы измеряют схожесть текстовых сегментов на основе общих последовательностей из n слов. Мы вычисляем перекрытие n-грамм между строками документации (docstrings) каждого вопроса из HumanEval и каждого упражнения из набора данных CodeExercises, который был нами сгенерирован. Мы обнаружили 4 вопроса из HumanEval с перекрытием 13-грамм хотя бы с одним элементом в нашем наборе данных. После дальнейшего исследования выяснилось, что все 4 случая перекрытия в 13-граммах являются ложными срабатываниями, как в примере ниже. Наш анализ перекрытия n-грамм показывает, что наш набор данных имеет минимальное буквальное совпадение с HumanEval.
HumanEval:
Вам дан непустой список положительных целых чисел. Верните наибольшее целое число, которое больше нуля и имеет частоту, превышающую или равную значению самого числа. Частота числа — это количество раз, которое оно встречается в списке.
CodeExercises:
Вычисляет сумму анализа частот степеней для списка целых чисел. Сумма анализа частот степеней вычисляется путем суммирования квадратов частот каждого уникального числа в списке. Частота числа — это количество раз, которое оно встречается в списке.
5.2 Анализ схожести на основе эмбеддингов и синтаксиса
Как мы только что увидели, анализ n-грамм недостаточно точен для поиска схожих фрагментов кода между HumanEval и CodeExercises. Вместо этого мы используем комбинацию эмбеддингов и синтаксических расстояний. Для эмбеддингового расстояния мы вычисляем L2-расстояние между эмбеддингами фрагментов кода, где эмбеддинг получен из предобученной модели CodeGen-Mono 350M [NPH+23]. Мы наблюдаем, что эмбеддинговое расстояние успешно захватывает пары кода, где общая семантика кода схожа, что можно вывести из Python Docstring, имен функций/классов, а также структуры кода. Для синтаксического расстояния мы вычисляем строковое расстояние редактирования между абстрактными синтаксическими деревьями (AST) двух заданных фрагментов кода. Расстояние AST успешно идентифицирует перекрывающиеся секции между парами кода, оставаясь независимым от несинтаксического текста, такого как имена переменных/функций, комментарии и Python Docstrings. Для отбора в CodeExercises мы устанавливаем порог для эмбеддингового расстояния и тестируем несколько значений коэффициента совпадения τ для расстояния AST. См. Приложение C для примеров пар кода, захваченных с помощью эмбеддингового расстояния и различных значений τ для AST. Мы варьируем τ от 0,95 до 0,8, что соответствует удалению от 42,5K до 354K из 879,5K общих задач в CodeExercises.
Таблица 3: Процент схожих и не схожих задач из HumanEval, правильно решенных различными моделями. Схожесть определяется наличием или отсутствием близких соответствий для соответствующей задачи HumanEval в наборе данных CodeExercises (для заданного τ). Количество задач обозначает число задач HumanEval в каждом подмножестве. Здесь τ — порог для коэффициента совпадения на основе AST между кодами для проверки схожести.
τ | Кол-во задач | phi-1 | phi-1 retrained on pruned data | StarCoder Prompted [*] | |
0.95 | похожие | 71 | 81.7% | 74.6% | 57.7% |
0.9 | похожие | 93 | 63.4% | 51.6% | 48.4% |
0.85 | похожие | 106 | 62.3% | 52.8% | 47.2% |
0.8 | похожие | 116 | 59.5% | 52.6% | 45.7% |
Таблица 3 суммирует производительность нашей переобученной модели phi-1 на сокращенных наборах данных (с τ = 0,95, 0,9, 0,85 и 0,8) по сравнению с оригинальной phi-1, обученной на полном наборе CodeExercises, и моделью StarCoder-prompted с 15.5 миллиардами параметров. Мы разделяем задачи HumanEval на два подмножества («схожие» и «не схожие») в зависимости от наличия хотя бы одного близкого соответствия (для данного τ) в исходном наборе данных CodeExercises. Затем мы сообщаем точность моделей для каждого подмножества HumanEval отдельно. Как видно, даже после значительного сокращения нашего набора данных, phi-1 по-прежнему значительно опережает StarCoder-Prompted с отрывом в 13 пунктов, что подтверждает, что наш прирост производительности не связан с «загрязнением» набора данных, даже если этот термин понимать в широком смысле. Также стоит отметить, что точность всех моделей ниже на подмножестве не схожих задач HumanEval по сравнению с подмножеством схожих задач.
6. Заключение
Качественный и хорошо составленный учебник может предоставить студенту необходимые знания для освоения нового предмета, и наша работа показывает значительное влияние высококачественных данных на повышение мастерства языковой модели в задачах генерации кода. Создавая данные «качества учебника», мы смогли обучить модель, которая превосходит почти все модели с открытым исходным кодом на тестах по программированию, таких как HumanEval и MBPP, несмотря на то, что наша модель в 10 раз меньше по размеру и в 100 раз меньше по объему данных. Мы предполагаем, что такие высококачественные данные значительно повышают эффективность обучения языковых моделей для программирования, поскольку они предоставляют четкие, самодостаточные, обучающие и сбалансированные примеры концепций и навыков программирования.
Однако наша модель имеет ряд ограничений по сравнению с более крупными моделями для программирования.
Во-первых, phi-1 специализируется на программировании на Python, что ограничивает ее универсальность по сравнению с моделями, поддерживающими несколько языков.
Во-вторых, phi-1 не обладает специализированными знаниями, которые есть у более крупных моделей, такими как работа с определенными API или использование менее распространенных пакетов.
Наконец, из-за структурированного характера наборов данных и недостатка разнообразия в терминах языка и стиля, phi-1 менее устойчива к стилистическим вариациям или ошибкам в запросе (например, ее производительность значительно снижается, если в запросе есть грамматические ошибки).
Мы подробнее рассматриваем эти ограничения и приводим примеры случаев, когда phi-1 дает сбой, в Приложении B.
Ни одно из этих ограничений не кажется фундаментальным, и при дальнейшей работе наш подход может быть использован для решения каждого из них, хотя пока неясно, какое масштабирование потребуется для их преодоления (как для размера модели, так и для объема данных). Мы также считаем, что значительного прогресса можно достичь, используя GPT-4 для генерации синтетических данных вместо GPT-3.5, поскольку мы заметили, что данные GPT-3.5 содержат много ошибок. Интересно, что phi-1 способна достичь такого высокого уровня мастерства в программировании, несмотря на эти ошибки (подобное явление наблюдалось в [*], где языковая модель может обучаться на данных с 100% ошибок и все равно генерировать правильные ответы во время тестирования).
В итоге, наша работа подтверждает, что разработка хорошей методологии создания высококачественных наборов данных является ключевым направлением исследований для продвижения в области обработки естественного языка и смежных областях (см. также [*]). Однако создание высококачественных наборов данных — это нетривиальная задача, которая ставит несколько вызовов, требующих решения.
Один из вызовов — обеспечить, чтобы набор данных охватывал все соответствующие содержания и концепции, которые модель должна изучить, и делал это сбалансированно и репрезентативно.
Другой вызов — обеспечить, чтобы набор данных был действительно разнообразным и не повторяющимся, чтобы модель не переобучалась на данных или не запоминала конкретные шаблоны или решения. Это требует поиска способов внедрения случайности и творчества в процесс генерации данных, сохраняя при этом качество и связность примеров.
Более того, даже после создания таких наборов данных у нас нет хорошей методологии для измерения и оценки уровня разнообразия и избыточности в данных. Например, если у нас есть набор данных с упражнениями по программированию, сложно определить, сколько различных вариаций каждого упражнения существует и как они распределены по набору данных. Наконец, поскольку сами языковые модели будут использоваться для генерации данных для будущих языковых моделей, это повышает актуальность этических и социальных последствий обучения таких моделей, таких как подотчетность, прозрачность и предвзятость данных и моделей, участвующих в этом процессе.
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[DFE+ 22] Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, and Christopher R´e. Flashattention: Fast and memory-efficient exact attention with io-awareness. Advances in Neural Information Processing Systems, 35:16344–16359, 2022.
[DLT+ 23] Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, and Tatsunori B Hashimoto. Alpacafarm: A simulation framework for methods that learn from human feedback. arXiv preprint arXiv:2305.14387, 2023.
[EL23] Ronen Eldan and Yuanzhi Li. Tinystories: How small can language models be and still speak coherent english? arXiv preprint arXiv:2305.07759, 2023. [GWS+ 23] Arnav Gudibande, Eric Wallace, Charlie Snell, Xinyang Geng, Hao Liu, Pieter Abbeel, Sergey Levine, and Dawn Song. The false promise of imitating proprietary llms. arXiv preprint arXiv:2305.15717, 2023.
[HBM+ 22] Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, Tom Hennigan, Eric Noland, Katherine Millican, George van den Driessche, Bogdan Damoc, Aurelia Guy, Simon Osindero, Karen Simonyan, Erich Elsen, Oriol Vinyals, Jack William Rae, and Laurent Sifre. An empirical analysis of compute-optimal large language model training. In Alice H. Oh, Alekh Agarwal, Danielle Belgrave, and Kyunghyun Cho, editors, Advances in Neural Information Processing Systems, 2022.
[HNA+ 17] Joel Hestness, Sharan Narang, Newsha Ardalani, Gregory Diamos, Heewoo Jun, Hassan Kianinejad, Md Mostofa Ali Patwary, Yang Yang, and Yanqi Zhou. Deep learning scaling is predictable, empirically. arXiv preprint arXiv:1712.00409, 2017.
[JWJ+ 23] Jaehun Jung, Peter West, Liwei Jiang, Faeze Brahman, Ximing Lu, Jillian Fisher, Taylor Sorensen, and Yejin Choi. Impossible distillation: from low-quality model to high-quality dataset & model for summarization and paraphrasing. arXiv preprint arXiv:2305.16635, 2023.
[KLA+ 22] Denis Kocetkov, Raymond Li, Loubna Ben Allal, Jia Li, Chenghao Mou, Carlos Mu˜noz Ferrandis, Yacine Jernite, Margaret Mitchell, Sean Hughes, Thomas Wolf, et al. The stack: 3 tb of permissively licensed source code. arXiv preprint arXiv:2211.15533, 2022.
[KMH+ 20] Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. Scaling laws for neural language models. arXiv preprint arXiv:2001.08361, 2020.
[LAZ+ 23] Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, et al. Starcoder: may the source be with you! arXiv preprint arXiv:2305.06161, 2023.
[LCC+ 22] Yujia Li, David Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, R´emi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, et al. Competition-level code generation with alphacode. Science, 378(6624):1092–1097, 2022.
[LGK+ 23] Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Harsha Nori, and Sergey Yekhanin. Differentially private synthetic data via foundation model apis 1: Images. arXiv preprint arXiv:2305.15560, 2023.
[LXWZ23] Jiawei Liu, Chunqiu Steven Xia, Yuyao Wang, and Lingming Zhang. Is your code generated by chatgpt really correct? rigorous evaluation of large language models for code generation. arXiv preprint arXiv:2305.01210, 2023.
[LXZ+ 23] Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, Qingwei Lin, and Daxin Jiang. Wizardcoder: Empowering code large language models with evol-instruct, 2023.
[LYR+ 23] Shayne Longpre, Gregory Yauney, Emily Reif, Katherine Lee, Adam Roberts, Barret Zoph, Denny Zhou, Jason Wei, Kevin Robinson, David Mimno, et al. A pretrainer’s guide to training data: Measuring the effects of data age, domain coverage, quality, & toxicity. arXiv preprint arXiv:2305.13169, 2023.
[MMJ+ 23] Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, Sahaj Agarwal, Hamid Palangi, and Ahmed Awadallah. Orca: Progressive learning from complex explanation traces of gpt-4. arXiv preprint arXiv:2306.02707, 2023.
[MRB+ 23] Niklas Muennighoff, Alexander M Rush, Boaz Barak, Teven Le Scao, Aleksandra Piktus, Nouamane Tazi, Sampo Pyysalo, Thomas Wolf, and Colin Raffel. Scaling data-constrained language models. arXiv preprint arXiv:2305.16264, 2023.
[NHX+ 23] Erik Nijkamp, Hiroaki Hayashi, Caiming Xiong, Silvio Savarese, and Yingbo Zhou. Codegen2: Lessons for training llms on programming and natural languages. arXiv preprint arXiv:2305.02309, 2023.
[NPH+ 22] Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong. Codegen: An open large language model for code with multi-turn program synthesis. arXiv preprint, 2022.
[NPH+ 23] Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong. Codegen: An open large language model for code with multi-turn program synthesis. ICLR, 2023.
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[SSZ+ 23] Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, and Ross Anderson. Model dementia: Generated data makes models forget. arXiv preprint arXiv:2305.17493, 2023
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[WKM+ 22] Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A Smith, Daniel Khashabi, and Hannaneh Hajishirzi. Self-instruct: Aligning language model with self generated instructions. arXiv preprint arXiv:2212.10560, 2022.
[WLG+ 23] Yue Wang, Hung Le, Akhilesh Deepak Gotmare, Nghi DQ Bui, Junnan Li, and Steven CH Hoi. Codet5+: Open code large language models for code understanding and generation. arXiv preprint arXiv:2305.07922, 2023.
[WTB+ 22] Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, and William Fedus. Emergent abilities of large language models. Transactions on Machine Learning Research, 2022. Survey Certification.
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A. Дополнительные примеры для Раздела 3
В Разделе 3 мы обсудили на нескольких примерах, как дообученные модели демонстрируют значительное улучшение по сравнению с базовой моделью при выполнении задач, которые не представлены в наборе данных для дообучения. Здесь мы предоставляем дополнительные примеры и детали, чтобы проиллюстрировать эти улучшения.
A.1 Дообучение (файнтюнинг) улучшает способность модели к пониманию
Следующий пример является сложным из-за обилия различных логических операторов, таких как «и» и «не», которые связывают множество утверждений. До файнтюнинга модель путается в логике, заложенной в утверждении. Она с трудом различает «элементы» и «индексы» и не уверена, какой массив использовать. Напротив, дообученная модель успешно идентифицирует все соответствующие массивы и индексы, корректно реализуя логические операторы.
Prompt: Input is an array A, an array B, an array C, an array E, a numpy matrix D. I want to find all the indices of D whose elements are in the union of B and C and whose row index is not in A and column index is in D. Loop through the elements in D. Return the list of indices.
Промпт: Входные данные: массив A, массив B, массив C, массив E, матрица numpy D. Найди все индексы матрицы D, элементы которых находятся в объединении B и C, и чей индекс строки не входит в A, а индекс столбца входит в D. Пройдись по элементам матрицы D. Верни список индексов.
# phi-1
indices = []
for i in range(D.shape[0]):
for j in range(D.shape[1]):
if D[i][j] in B or D[i][j] in C:
if i not in A and j in D:
indices.append((i,j))
return indices# phi-1-base
indices = []
for i in range(len(D)):
for j in range(len(D[i])):
if D[i][j] in B and D[i][j] not in A:
indices.append(j)
return indices# phi-1-small
indices = []
for i in range(D.shape[1]):
if D[0][i] in B and D[0][i] not in A and D[i][0] in C and D[i][0] not in E:
indices.append(i)
return indicesA.2 Дообучение улучшает способность модели использовать внешние библиотеки
Пример с PyTorch.
В этом примере с использованием PyTorch мы просим модель написать модифицированный шаг обновления градиента:
Prompt: Write a pytorch function. The input is a model, take the gradient of each parameter of the model, do an SVD of each gradient to get U, Sigma, V, take the top k singular values of Sigma as Sigmak, then do a update step to the parameter using Uk*Sigmak * Vk times the norm of the parameter.
Промпт: Напиши функцию на PyTorch. Входные данные — это модель. Возьми градиент каждого параметра модели, выполни сингулярное разложение (SVD) каждого градиента, чтобы получить U, Sigma, V, возьми топ-k сингулярных значений Sigma как Sigma k, затем выполни шаг обновления параметра, используя Uk * Sigma k * Vk, умноженное на норму параметра.
# phi-1
...
for p in model.parameters():
if p.grad is not None:
U, Sigma, V = p.grad.svd()
Sigmak = Sigma[:k].diag()
p.data.add_(torch.mm(U[:,:k], torch.mm(Sigmak, V[:k,:])).mul_(norm))# phi-1-base
...
self.model = model
self.k = k
self.eps = eps
self.max_iter = max_iter
self.verbose = verbose
self.svd_u = None
self.svd_sigma = None
self.svd_v = None
self.svd_k = None
self.svd_u_k = None
...# phi-1-small
def svd(x):
u, s, v = np.linalg.svd(x)
return u, s, v
def update_parameter(parameter, grad):
u, s, v = svd(grad)
parameter = u[:, :k]
np.diag(s[:k]) v[:k, :]
parameter += np.diag(sigmoid(parameter))
return parameterКод, созданный моделью phi-1-small, демонстрирует недостаточное понимание API и ограничения в понимании задачи, что приводит к нескольким значительным ошибкам. Во-первых, он использует np.linalg.svd(x), что несовместимо с тензорами PyTorch. Во-вторых, он ошибочно присваивает результат SVD непосредственно параметру, отклоняясь от инструкции в запросе, где требуется добавить его. С другой стороны, phi-1-base полностью теряется и выдает лишь последовательность бессмысленных определений. Это указывает на то, что улучшение способности модели к логическому рассуждению (даже для простых функций) может значительно повысить общую способность модели к написанию кода.
Пример с Pyplot
Последний пример связан с использованием API Pyplot. Модель обычно хорошо справляется с Pyplot, поэтому мы разработали сложную задачу, попросив модель реализовать анимацию.
Prompt: Create an x array that are integers from 1 to 20, y array that is equal to the
elementwise cos of x divided by element-wise sqrt(x + 1). Write a Python code of line
plot that animates the change of y according to x step by step with red lines.
However, during the animation, when x[i] is larger than 11, change the animation line
color from red to green.Промпт: Создай массив x, состоящий из целых чисел от 1 до 20, и массив y, равный cos x каждого элемента, деленному на квадратный корень из (x + 1) каждого элемента. Напиши код на Python для построения линейного графика, который анимирует изменение y в зависимости от x шаг за шагом с использованием красных линий. Однако во время анимации, когда x[i] становится больше 11, изменит цвет линии анимации с красного на зеленый.
# phi-1
...
x = np.arange(1, 21)
y = np.cos(x) / np.sqrt(x + 1)
fig, ax = plt.subplots()
line, = ax.plot([], [], color='red')
...
ax.set_title('Animation of Cosine and Cosine-Square-Root')
def animate(i):
if x[i] > 11:
line.set_color('green')
else:
line.set_color('red')
line.set_data(x[:i+1], y[:i+1])
return line,
anim = animation.FuncAnimation(fig, animate, frames=len(x), interval=500, blit=True)
plt.show()# phi-1-base
...
fig, ax = plt.subplots()
x = np.arange(1, 21)
y = np.cos(x) / np.sqrt(x + 1)
line, = ax.plot([], [], lw=2)
def init():
line.set_data([], [])
return line,
def animate(i):
if x[i] > 11:
line.set_color('green')
else:
line.set_color('red')
return line,
anim = FuncAnimation(fig, animate, init_func=init, frames=len(x), interval=50, blit=True)# phi-1-small
...
fig, ax = plt.subplots()
x_array = list(range(1, 21))
y_array = [math.cos(xi/10) for xi in x_array]
def animate(i):
...
ax.plot(x_array, y_array)
if x_array[i] > 11:
color = "red"
else:
color = "green"
ax.scatter(x_array[i],
y_array[i], color=color)
return ax
ani = animation.FuncAnimation(fig, animate, frames=len(x_array), interval=50, blit=True)
plt.show()phi-1-small выдает некорректный результат. С точки зрения API, модель не понимает требование «линейный график» и использует только точечный график (и даже он реализован неправильно). phi-1-base правильно понимает шаблон, но упускает основную функцию для обновления линейного графика на каждой итерации.
B. Ограничения модели phi-1
Хотя дообучение на простых упражнениях значительно улучшает общую производительность модели, существуют определенные ограничения, присущие нашей модели, которые невозможно преодолеть только за счет файнтюнинга. Во-первых, наша модель имеет всего 1,3 миллиарда параметров и обучалась на 7 миллиардах токенов, что ограничивает ее способность справляться с более сложными задачами, такими как разработка сложного приложения на Flask, по сравнению с другими моделями, такими как Starcoder. Помимо ограничений нашей модели в плане универсальности по сравнению с StarCoder или ChatGPT, мы также выделили несколько других слабых сторон:
Чувствительность к вариациям в запросах.
Наша модель чувствительна к различным изменениям в запросах. Во-первых, ее производительность значительно снижается с увеличением длины запроса, так как она склонна игнорировать, забывать или неправильно интерпретировать части запроса, если он слишком длинный. Например, наша модель не справляется, когда мы увеличиваем количество слоев с 3 до 4 в следующем случае. Мы предполагаем, что эта проблема возникает из-за того, что наши упражнения в основном состоят из коротких запросов. Кроме того, результат генерации может качественно отличаться при незначительном изменении запроса. В этом случае, с добавлением команды import torch, модель часто успешно справляется с задачей, которая ранее вызывала у нее затруднения.
Пример запроса 1:
Create a neural network class in Pytorch with 3 layers. Implement a new "rr" method to this new function: It takes input x. Apply the first layer on x and assign the output to y, then apply the second layer on y and assign the output to z, then apply the third layer on z and assign it to w, then sum up y, z, w and assign it to Q. Return Q
Создай класс нейронной сети на PyTorch с 3 слоями. Реализуй новый метод "rr" для этой функции: Он принимает входные данные x. Примени первый слой к x и присвой результат y, затем примени второй слой к y и присвой результат z, затем примени третий слой к z и присвой результат w, затем сложи y, z, w и присвой результат Q. Верни Q.
class NeuralNetwork(nn.Module):
def __init__(self):
super(NeuralNetwork, self).__init__()
self.layer1 = nn.Linear(2, 5)
self.layer2 = nn.Linear(5, 3)
self.layer3 = nn.Linear(3, 1)
def rr(self, x):
y = self.layer1(x)
z = self.layer2(y)
w = self.layer3(z)
Q = y + z + w
return QПример запроса 2:
Create a neural network class in Pytorch with 4 layers. Implement a new "rr" method to this new function: It takes input x. Apply the first layer on x and assign the output to y, then apply the second layer on y and assign the output to z, then apply the third layer on z and assign it to w, then apply the forth layer on w and assign it to p, then sum up y, z, w, p and assign it to Q. Return Q.
Создай класс нейронной сети на PyTorch с 4 слоями. Реализуй новый метод "rr" для этой функции: Он принимает входные данные x. Примени первый слой к x и присвой результат y, затем примени второй слой к y и присвой результат z, затем примени третий слой к z и присвой результат w, затем примени четвертый слой к w и присвой результат p, затем сложи y, z, w, p и присвой результат Q. Верни Q.
class NeuralNetwork:
def __init__(self):
self.layers = []
def add_layer(self, layer):
self.layers.append(layer)
...
def rr(self, x):
y = self.forward(x)
z = self.forward(y)
w = self.forward(z)
p = self.forward(w)
Q = y + z + w + p
return QПример запроса 3:
import torchCreate a neural network class in Pytorch with 4 layers. Implement a new "rr" method to this new function: It takes input x. Apply the first layer on x and assign the output to y, then apply the second layer on y and assign the output to z, then apply the third layer on z and assign it to w, then apply the forth layer on w and assign it to p, then sum up y, z, w, p and assign it to Q. Return Q.
import torchСоздай класс нейронной сети на PyTorch с 4 слоями. Реализуй новый метод "rr" для этой функции: Он принимает входные данные x. Примени первый слой к x и присвой результат y, затем примени второй слой к y и присвой результат z, затем примени третий слой к z и присвой результат w, затем примени четвертый слой к w и присвой результат p, затем сложи y, z, w, p и присвой результат Q. Верни Q.
class NeuralNetwork(torch.nn.Module):
def __init__(self):
super(NeuralNetwork, self).__init__()
self.layer1 = torch.nn.Linear(10, 20)
...
def forward(self, x):
x = torch.nn.functional.relu(self.layer1(x))
y = torch.nn.functional.relu(self.layer2(x))
z = torch.nn.functional.relu(self.layer3(y))
w = torch.nn.functional.relu(self.layer4(z))
p = torch.nn.functional.relu(self.output(w))
Q = p + y + z + w
return QЧувствительность к естественным языковым запросам
Модель phi-1 демонстрирует меньшую устойчивость к обработке естественного языка по сравнению с ChatGPT или StarCoder, особенно в случае неоднозначных запросов. Это может быть связано с тем, что мы исключили определенные типы данных из процесса обучения, чтобы гарантировать качество на уровне учебника.
Например, наша модель испытывает трудности с термином «неизменный» (unchanged) и с интерпретацией нумерованных списков в запросе.
Пример запроса 1:
Alice is moving a point along x,y axes at every iteration. Every time Alice moves the point randomly with one of the options: (1). x increases by 2, y decreases by 5; (2). x increases by 1, y decreases by 2, (3). x stays unchanged, y increase by 4. Simulate the movement of the points.
Алиса перемещает точку вдоль осей x и y на каждой итерации. Каждый раз Алиса перемещает точку случайным образом одним из вариантов: (1) x увеличивается на 2, y уменьшается на 5; (2) x увеличивается на 1, y уменьшается на 2; (3) x остается неизменным, y увеличивается на 4. Смоделируй движение точки.
x, y = 0, 0
for i in range(10):
move = random.choice([1, 2,3])
if move == 1:
x += 2
y -= 5
elif move == 2:
x += 1
y -= 2
elif move == 3:
x = 0
y += 4
return f"Alice's final position is ({x}, {y})."Пример запроса 2:
Alice is moving a point along x,y axes at every iteration. Every time Alice moves the point randomly with one of the options: (1). x increases by 2, y decreases by 5; (2). x increases by 1, y decreases by 2, (3). x stays at x, y increase by 4. Simulate the movement of the points.
Алиса перемещает точку вдоль осей x и y на каждой итерации. Каждый раз Алиса перемещает точку случайным образом одним из вариантов: (1) x увеличивается на 2, y уменьшается на 5; (2) x увеличивается на 1, y уменьшается на 2; (3) x остается равным x, y увеличивается на 4. Смоделируй движение точки.
x, y = 0, 0
for i in range(10):
move = random.choice([1, 2, 3])
if move == 1:
x += 2
y -= 5
elif move == 2:
x += 1
y -= 2
elif move == 3:
x = x
y += 4
print(f"Alice moved {move}
point to ({x}, {y})")Пример запроса 3:
Alice is moving a point along x,y axes at every iteration. Every time Alice moves the point randomly with one of the options: (1). move by (2, -5); (2). move by (1, 2); (3). move by (0, 4); Simulate the movement of the points.
Алиса перемещает точку вдоль осей x и y на каждой итерации. Каждый раз Алиса перемещает точку случайным образом одним из вариантов: (1) перемещение на (2, -5); (2) перемещение на (1, 2); (3) перемещение на (0, 4); Смоделируй движение точки.
x, y = 0, 0
for i in range(n):
move = random.choice([(1, 2), (2, -5), (1, 2), (3, 0), (0, 4)])
x += move[0]
y += move[1]
return f"Alice moved {x} units to the right and {y} units down after {n} iterations."
# Note: the model hallucinates the moves (1, 2), (3, 0).Эти примеры показывают, что модель phi-1 может испытывать трудности с интерпретацией естественного языка, особенно если присутствуют неоднозначные или сложные конструкции. Это подчеркивает необходимость дальнейшего улучшения модели в плане обработки естественного языка и повышения ее устойчивости к вариативным запросам.
Плохая способность к счету и пространственному мышлению
Одним из основных ограничений нашей модели, особенно в сравнении с альтернативами, такими как StarCoder, является ее производительность на задачах, связанных с подсчетом и пространственным мышлением. Модель с трудом поддерживает точные данные о количестве и расположении элементов в сцене. Чтобы проиллюстрировать это, рассмотрим следующий пример:
Пример запроса:
Generate a
tkinterapplication, I want two textfields side by side at the top, three buttons at the bottom, one named A on the left, one named B on the right, one named C at the middle.Создай приложение на
tkinter. Мне нужно два текстовых поля, расположенных рядом в верхней части, три кнопки в нижней части: одна с именем A слева, одна с именем B справа и одна с именем C по центру.
# phi-1
...
text_a = tk.Text(root, width=30, height=5)
text_b = tk.Text(root, width=30, height=5)
text_c = tk.Text(root, width=30, height=5)
# Create the buttons
button_a = tk.Button(root, text="A", width=10, height=2)
button_b = tk.Button(root, text="B", width=10, height=2)
button_c = tk.Button(root, text="C", width=10, height=2)
# Place the text fields and buttons in the top row
text_a.grid(row=0, column=0, padx=5, pady=5)
text_b.grid(row=0, column=1, padx=5, pady=5)
text_c.grid(row=0, column=2, padx=5, pady=5)
# Place the buttons in the bottom row
button_a.grid(row=1, column=0, columnspan=3, padx=5, pady=5)
button_b.grid(row=1, column=1, columnspan=3, padx=5, pady=5)
button_c.grid(row=1, column=2, columnspan=3, padx=5, pady=5)
...# phi-1-small
window = tk.Tk()
window.title("TextFields")
# Create the left and right textfields
text1 = tk.Text(window, text="A")
text1.pack()
text2 = tk.Text(window, text="B")
text2.pack()
# Create the middle button
button = tk.Button(window, text="C")
button.pack()
# Start the tkinter application
window.mainloop()# phi-1-base
root = tk.Tk()
root.title("Text Fields")
root.geometry("300x200")
root.resizable(False, False)
root.configure(background="white")
root.configure(font=("Arial", 12))
root.configure(foreground="black")
root.configure(relief="groove")
root.configure(padx=10, pady=10)
root.configure(state="disabled")
# The model keeps outputting nonsensical code.Несмотря на улучшения, достигнутые за счет дообучения, наша модель по-прежнему испытывает трудности с подсчетом и пространственным мышлением. Она создает лишнее текстовое поле и неправильно размещает кнопку в сцене.
C. Примеры для Раздела 5
В этом разделе мы предоставляем примеры пар кода, с разными коэффициентами совпадения AST. Кроме того, мы приводим пример пары кода, полученной с использованием эмбеддингового расстояния в качестве меры схожести.
Коэффициент совпадения AST = 1.0
Здесь задачи на программирование требуют одинакового логического рассуждения, хотя формулировки запросов могут значительно отличаться. В частности, в запросе используется реальное событие (например, расстояние между отверстиями на линии), чтобы неявно обучить модели базовой задаче нахождения ближайшей пары элементов в массиве.
HumanEval
from typing import List, Tuple
def find_closest_elements(numbers: List[float]) -> Tuple[float, float]:
""" From a supplied list of numbers (of
length at least two) select and return two
that are the closest to each
other and return them in order (smaller
number, larger number).
>>> find_closest_elements([1.0, 2.0, 3.0,
4.0, 5.0, 2.2])
(2.0, 2.2)
>>> find_closest_elements([1.0, 2.0, 3.0,
4.0, 5.0, 2.0])
(2.0, 2.0)
"""
numbers.sort()
min_diff = float('inf')
closest_pair = None
for i in range(len(numbers) - 1):
diff = numbers[i+1] - numbers[i]
if diff < min_diff:
min_diff = diff
closest_pair = (numbers[i], numbers[i
+1])
return closest_pairCodeExercises
from typing import List, Tuple
def find_closest_two_holes(holes: List[int]) -> (int, int):
"""
Finds the two closest holes on a line.
Args:
holes: A list of integers representing
the positions of holes on a line.
Returns:
A tuple of two integers representing the
positions of the two closest holes on the
line.
"""
holes.sort()
min_distance = float('inf')
closest_holes = None
for i in range(len(holes) - 1):
distance = holes[i+1] - holes[i]
if distance < min_distance:
min_distance = distance
closest_holes = (holes[i], holes[i+1])
return closest_holesКоэффициент совпадения AST = 0.96
Здесь две задачи используют схожие логические рассуждения и концепции программирования, но их запросы требуют выполнения разных задач, например, возвращение пары чисел в отличие от вычисления их среднего значения.
HumanEval
from typing import List
def find_closest_elements(numbers: List[float]) -> Tuple[float, float]:
""" From a supplied list of numbers (of
length at least two) select and return two
that are the closest to each
other and return them in order (smaller
number, larger number).
>>> find_closest_elements([1.0, 2.0, 3.0,
4.0, 5.0, 2.2])
(2.0, 2.2)
>>> find_closest_elements([1.0, 2.0, 3.0,
4.0, 5.0, 2.0])
(2.0, 2.0)
"""
numbers.sort()
min_diff = float('inf')
closest_pair = None
for i in range(len(numbers) - 1):
diff = numbers[i+1] - numbers[i]
if diff < min_diff:
min_diff = diff
closest_pair = (numbers[i], numbers[i+1])
return closest_pairCodeExercises
from typing import List
def find_closest_pair_average(li: List[int]) -> float:
"""
Returns the average of the two integers in
the list that are closest to each other.
If there are multiple pairs with the same
minimum difference, the function returns the
average of the first pair it encounters.
Args:
- li: a list of integers
Returns:
- a float representing the average of the two
integers in the list that are closest to
each other
"""
li.sort()
min_diff = float('inf')
closest_pair = None
for i in range(len(li)-1):
diff = li[i+1] - li[i]
if diff < min_diff:
min_diff = diff
closest_pair = (li[i], li[i+1])
return sum(closest_pair) / 2Коэффициент совпадения AST ≤ 0.9
Когда коэффициент совпадения AST ≤ 0.9, пары кода становятся менее схожими, так как их структура и логика начинают значительно отличаться. Здесь уровень совпадения AST (абстрактного синтаксического дерева) составляет 0.9 и 0.83 соответственно.
HumanEval
from typing import List
def all_prefixes(string: str) -> List[str]:
""" Return list of all prefixes from
shortest to longest of the input string
>>> all_prefixes('abc')
['a', 'ab', 'abc']
"""
prefixes = []
for i in range(len(string)):
prefixes.append(string[:i+1])
return prefixesCodeExercises
from typing import List
def increase_after_each(li: List[int]) -> List[int]:
"""
Given a list of integers, returns a new list
where each element is increased by the
number of elements in the original list that
come after it.
Args:
- li: A list of integers
Returns:
- A new list of integers where each element
is increased by the number of elements in
the original list that come after it.
"""
result = []
for i in range(len(li)):
result.append(li[i] + len(li[i+1:]))
return resultHumanEval
from typing import List
def rescale_to_unit(numbers: List[float]) -> List[float]:
""" Given list of numbers (of at least two
elements), apply a linear transform to that
list, such that the smallest number will
become 0 and the largest will become 1
>>> rescale_to_unit([1.0, 2.0, 3.0, 4.0,
5.0])
[0.0, 0.25, 0.5, 0.75, 1.0]
"""
min_num = min(numbers)
max_num = max(numbers)
return [(num - min_num) / (max_num - min_num) for num in numbers]CodeExercises
from typing import List
def frequency_ranges_plot(values: List[float]) -> List[List[int]]:
"""
Returns a list of lists where each inner list
represents a frequency range and contains
the count of values
that fall within that range. The ranges are
determined by dividing the range of values
into 10 equal parts.
Args:
- values: A list of float values
Returns:
- A list of lists where each inner list
contains two integers representing the lower
and upper bounds of the range
and the count of values that fall within that
range.
"""
min_val = min(values)
max_val = max(values)
range_size = (max_val - min_val) / 10
ranges = [[min_val + i*range_size, min_val + (i+1)*range_size, 0] for i in ange(10)]
for val in values:
for i, r in enumerate(ranges):
if r[0] <= val < r[1]:
ranges[i][2] += 1
break
return [[int(r[0]), int(r[1]), r[2]] for r in ranges]Эмбеддинговое расстояние = 0.16
Здесь две задачи имеют схожие Python Docstrings, имена функций, а также структуру кода, что можно выявить с помощью L2-расстояния между нормализованными эмбеддингами CodeGen-Mono 350M для каждой из них.
HumanEval
def sum_product(numbers: List[int]) -> Tuple[int, int]:
""" For a given list of integers, return a
tuple consisting of a sum and a product of
all the integers in a list.
Empty sum should be equal to 0 and empty
product should be equal to 1.
>>> sum_product([])
(0, 1)
>>> sum_product([1, 2, 3, 4])
(10, 24)
"""
sum_value = 0
prod_value = 1
for n in numbers:
sum_value += n
prod_value *= n
return sum_value, prod_valueCodeExercises
from typing import List, Tuple
def all_numbers_sum_product(numbers: List[int]) -> Tuple[int,int]:
"""
Returns a tuple containing the sum and
product of all the numbers in the input list.
Args:
- numbers (List[int]): a list of integers
Returns:
- a tuple containing two integers:
- the sum of all the numbers in the input
list
- the product of all the numbers in the
input list
"""
sum_of_numbers = 0
product_of_numbers = 1
for num in numbers:
sum_of_numbers += num
product_of_numbers *= num
return (sum_of_numbers, product_of_numbers)-
07.09.23 16:24
CherryTeam
Cherry Team atlyginimų skaičiavimo programa yra labai naudingas įrankis įmonėms, kai reikia efektyviai valdyti ir skaičiuoti darbuotojų atlyginimus. Ši programinė įranga, turinti išsamias funkcijas ir patogią naudotojo sąsają, suteikia daug privalumų, kurie padeda supaprastinti darbo užmokesčio skaičiavimo procesus ir pagerinti finansų valdymą. Štai keletas pagrindinių priežasčių, kodėl Cherry Team atlyginimų skaičiavimo programa yra naudinga įmonėms: Automatizuoti ir tikslūs skaičiavimai: Atlyginimų skaičiavimai rankiniu būdu gali būti klaidingi ir reikalauti daug laiko. Programinė įranga Cherry Team automatizuoja visą atlyginimų skaičiavimo procesą, todėl nebereikia atlikti skaičiavimų rankiniu būdu ir sumažėja klaidų rizika. Tiksliai apskaičiuodama atlyginimus, įskaitant tokius veiksnius, kaip pagrindinis atlyginimas, viršvalandžiai, premijos, išskaitos ir mokesčiai, programa užtikrina tikslius ir be klaidų darbo užmokesčio skaičiavimo rezultatus. Sutaupoma laiko ir išlaidų: Darbo užmokesčio valdymas gali būti daug darbo jėgos reikalaujanti užduotis, reikalaujanti daug laiko ir išteklių. Programa Cherry Team supaprastina ir pagreitina darbo užmokesčio skaičiavimo procesą, nes automatizuoja skaičiavimus, generuoja darbo užmokesčio žiniaraščius ir tvarko išskaičiuojamus mokesčius. Šis automatizavimas padeda įmonėms sutaupyti daug laiko ir pastangų, todėl žmogiškųjų išteklių ir finansų komandos gali sutelkti dėmesį į strategiškai svarbesnę veiklą. Be to, racionalizuodamos darbo užmokesčio operacijas, įmonės gali sumažinti administracines išlaidas, susijusias su rankiniu darbo užmokesčio tvarkymu. Mokesčių ir darbo teisės aktų laikymasis: Įmonėms labai svarbu laikytis mokesčių ir darbo teisės aktų, kad išvengtų baudų ir teisinių problemų. Programinė įranga Cherry Team seka besikeičiančius mokesčių įstatymus ir darbo reglamentus, užtikrindama tikslius skaičiavimus ir teisinių reikalavimų laikymąsi. Programa gali dirbti su sudėtingais mokesčių scenarijais, pavyzdžiui, keliomis mokesčių grupėmis ir įvairių rūšių atskaitymais, todėl užtikrina atitiktį reikalavimams ir kartu sumažina klaidų riziką. Ataskaitų rengimas ir analizė: Programa Cherry Team siūlo patikimas ataskaitų teikimo ir analizės galimybes, suteikiančias įmonėms vertingų įžvalgų apie darbo užmokesčio duomenis. Ji gali generuoti ataskaitas apie įvairius aspektus, pavyzdžiui, darbo užmokesčio paskirstymą, išskaičiuojamus mokesčius ir darbo sąnaudas. Šios ataskaitos leidžia įmonėms analizuoti darbo užmokesčio tendencijas, nustatyti tobulintinas sritis ir priimti pagrįstus finansinius sprendimus. Pasinaudodamos duomenimis pagrįstomis įžvalgomis, įmonės gali optimizuoti savo darbo užmokesčio strategijas ir veiksmingai kontroliuoti išlaidas. Integracija su kitomis sistemomis: Cherry Team programinė įranga dažnai sklandžiai integruojama su kitomis personalo ir apskaitos sistemomis. Tokia integracija leidžia automatiškai perkelti atitinkamus duomenis, pavyzdžiui, informaciją apie darbuotojus ir finansinius įrašus, todėl nebereikia dubliuoti duomenų. Supaprastintas duomenų srautas tarp sistemų padidina bendrą efektyvumą ir sumažina duomenų klaidų ar neatitikimų riziką. Cherry Team atlyginimų apskaičiavimo programa įmonėms teikia didelę naudą - automatiniai ir tikslūs skaičiavimai, laiko ir sąnaudų taupymas, atitiktis mokesčių ir darbo teisės aktų reikalavimams, ataskaitų teikimo ir analizės galimybės bei integracija su kitomis sistemomis. Naudodamos šią programinę įrangą įmonės gali supaprastinti darbo užmokesčio skaičiavimo procesus, užtikrinti tikslumą ir atitiktį reikalavimams, padidinti darbuotojų pasitenkinimą ir gauti vertingų įžvalgų apie savo finansinius duomenis. Programa Cherry Team pasirodo esanti nepakeičiamas įrankis įmonėms, siekiančioms efektyviai ir veiksmingai valdyti darbo užmokestį. https://cherryteam.lt/lt/
-
08.10.23 01:30
davec8080
The "Shibarium for this confirmed rug pull is a BEP-20 project not related at all to Shibarium, SHIB, BONE or LEASH. The Plot Thickens. Someone posted the actual transactions!!!! https://bscscan.com/tx/0xa846ea0367c89c3f0bbfcc221cceea4c90d8f56ead2eb479d4cee41c75e02c97 It seems the article is true!!!! And it's also FUD. Let me explain. Check this link: https://bscscan.com/token/0x5a752c9fe3520522ea88f37a41c3ddd97c022c2f So there really is a "Shibarium" token. And somebody did a rug pull with it. CONFIRMED. But the "Shibarium" token for this confirmed rug pull is a BEP-20 project not related at all to Shibarium, SHIB, BONE or LEASH.
-
24.06.24 04:31
tashandiarisha
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26.06.24 18:46
Jacobethannn098
LEGAL RECOUP FOR CRYPTO THEFT BY ADRIAN LAMO HACKER
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26.06.24 18:46
Jacobethannn098
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04.07.24 04:49
ZionNaomi
For over twenty years, I've dedicated myself to the dynamic world of marketing, constantly seeking innovative strategies to elevate brand visibility in an ever-evolving landscape. So when the meteoric rise of Bitcoin captured my attention as a potential avenue for investment diversification, I seized the opportunity, allocating $20,000 to the digital currency. Witnessing my investment burgeon to an impressive $70,000 over time instilled in me a sense of financial promise and stability.However, amidst the euphoria of financial growth, a sudden and unforeseen oversight brought me crashing back to reality during a critical business trip—I had misplaced my hardware wallet. The realization that I had lost access to the cornerstone of my financial security struck me with profound dismay. Desperate for a solution, I turned to the expertise of Daniel Meuli Web Recovery.Their response was swift . With meticulous precision, they embarked on the intricate process of retracing the elusive path of my lost funds. Through their unwavering dedication, they managed to recover a substantial portion of my investment, offering a glimmer of hope amidst the shadows of uncertainty. The support provided by Daniel Meuli Web Recovery extended beyond mere financial restitution. Recognizing the imperative of fortifying against future vulnerabilities, they generously shared invaluable insights on securing digital assets. Their guidance encompassed crucial aspects such as implementing hardware wallet backups and fortifying security protocols, equipping me with recovered funds and newfound knowledge to navigate the digital landscape securely.In retrospect, this experience served as a poignant reminder of the critical importance of diligence and preparedness in safeguarding one's assets. Thanks to the expertise and unwavering support extended by Daniel Meuli Web Recovery, I emerged from the ordeal with renewed resilience and vigilance. Empowered by their guidance and fortified by enhanced security measures, I now approach the future with unwavering confidence.The heights of financial promise to the depths of loss and back again has been a humbling one, underscoring the volatility and unpredictability inherent in the digital realm. Yet, through adversity, I have emerged stronger, armed with a newfound appreciation for the importance of diligence, preparedness, and the invaluable support of experts like Daniel Meuli Web Recovery.As I persist in traversing the digital landscape, I do so with a judicious blend of vigilance and fortitude, cognizant that with adequate safeguards and the backing of reliable confidants, I possess the fortitude to withstand any adversity that may arise. For this, I remain eternally appreciative. Email Danielmeuliweberecovery @ email . c om WhatsApp + 393 512 013 528
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13.07.24 21:13
michaelharrell825
In 2020, amidst the economic fallout of the pandemic, I found myself unexpectedly unemployed and turned to Forex trading in hopes of stabilizing my finances. Like many, I was drawn in by the promise of quick returns offered by various Forex robots, signals, and trading advisers. However, most of these products turned out to be disappointing, with claims that were far from reality. Looking back, I realize I should have been more cautious, but the allure of financial security clouded my judgment during those uncertain times. Amidst these disappointments, Profit Forex emerged as a standout. Not only did they provide reliable service, but they also delivered tangible results—a rarity in an industry often plagued by exaggerated claims. The positive reviews from other users validated my own experience, highlighting their commitment to delivering genuine outcomes and emphasizing sound financial practices. My journey with Profit Forex led to a net profit of $11,500, a significant achievement given the challenges I faced. However, my optimism was short-lived when I encountered obstacles trying to withdraw funds from my trading account. Despite repeated attempts, I found myself unable to access my money, leaving me frustrated and uncertain about my financial future. Fortunately, my fortunes changed when I discovered PRO WIZARD GIlBERT RECOVERY. Their reputation for recovering funds from fraudulent schemes gave me hope in reclaiming what was rightfully mine. With a mixture of desperation and cautious optimism, I reached out to them for assistance. PRO WIZARD GIlBERT RECOVERY impressed me from the start with their professionalism and deep understanding of financial disputes. They took a methodical approach, using advanced techniques to track down the scammers responsible for withholding my funds. Throughout the process, their communication was clear and reassuring, providing much-needed support during a stressful period. Thanks to PRO WIZARD GIlBERT RECOVERY's expertise and unwavering dedication, I finally achieved a resolution to my ordeal. They successfully traced and retrieved my funds, restoring a sense of justice and relief. Their intervention not only recovered my money but also renewed my faith in ethical financial services. Reflecting on my experience, I've learned invaluable lessons about the importance of due diligence and discernment in navigating the Forex market. While setbacks are inevitable, partnering with reputable recovery specialists like PRO WIZARD GIlBERT RECOVERY can make a profound difference. Their integrity and effectiveness have left an indelible mark on me, guiding my future decisions and reinforcing the value of trustworthy partnerships in achieving financial goals. I wholeheartedly recommend PRO WIZARD GIlBERT RECOVERY to anyone grappling with financial fraud or disputes. Their expertise and commitment to client satisfaction are unparalleled, offering a beacon of hope in challenging times. Thank you, PRO WIZARD GIlBERT RECOVERY, for your invaluable assistance in reclaiming what was rightfully mine. Your service not only recovered my funds but also restored my confidence in navigating the complexities of financial markets with greater caution and awareness. Email: prowizardgilbertrecovery(@)engineer.com Homepage: https://prowizardgilbertrecovery.xyz WhatsApp: +1 (516) 347‑9592
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17.07.24 02:26
thompsonrickey
In the vast and often treacherous realm of online investments, I was entangled in a web of deceit that cost me nearly $45,000. It all started innocuously enough with an enticing Instagram profile promising lucrative returns through cryptocurrency investment. Initially, everything seemed promising—communications were smooth, and assurances were plentiful. However, as time passed, my optimism turned to suspicion. Withdrawal requests were met with delays and excuses. The once-responsive "investor" vanished into thin air, leaving me stranded with dwindling hopes and a sinking feeling in my gut. It became painfully clear that I had been duped by a sophisticated scheme designed to exploit trust and naivety. Desperate to recover my funds, I turned to online forums where I discovered numerous testimonials advocating for Muyern Trust Hacker. With nothing to lose, I contacted them, recounting my ordeal with a mixture of skepticism and hope. Their swift response and professional demeanor immediately reassured me that I had found a lifeline amidst the chaos. Muyern Trust Hacker wasted no time in taking action. They meticulously gathered evidence, navigated legal complexities, and deployed their expertise to expedite recovery. In what felt like a whirlwind of activity, although the passage of time was a blur amidst my anxiety, they achieved the seemingly impossible—my stolen funds were returned. The relief I felt was overwhelming. Muyern Trust Hacker not only restored my financial losses but also restored my faith in justice. Their commitment to integrity and their relentless pursuit of resolution were nothing short of remarkable. They proved themselves as recovery specialists and guardians against digital fraud, offering hope to victims like me who had been ensnared by deception. My gratitude knows no bounds for Muyern Trust Hacker. Reach them at muyerntrusted @ m a i l - m e . c o m AND Tele gram @ muyerntrusthackertech
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18.07.24 20:13
austinagastya
I Testify For iBolt Cyber Hacker Alone - For Crypto Recovery Service I highly suggest iBolt Cyber Hacker to anyone in need of bitcoin recovery services. They successfully recovered my bitcoin from a fake trading scam with speed and efficiency. This crew is trustworthy, They kept me updated throughout the procedure. I thought my bitcoin was gone, I am so grateful for their help, If you find yourself in a similar circumstance, do not hesitate to reach out to iBolt Cyber Hacker for assistance. Thank you, iBOLT, for your amazing customer service! Please be cautious and contact them directly through their website. Email: S u p p o r t @ ibolt cyber hack . com Cont/Whtp + 3. .9 .3. .5..0. .9. 2. 9. .0 .3. 1 .8. Website: h t t p s : / / ibolt cyber hack . com /
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27.08.24 12:50
James889900
All you need is to hire an expert to help you accomplish that. If there’s any need to spy on your partner’s phone. From my experience I lacked evidence to confront my husband on my suspicion on his infidelity, until I came across ETHICALAHCKERS which many commend him of assisting them in their spying mission. So I contacted him and he provided me with access into his phone to view all text messages, call logs, WhatsApp messages and even her location. This evidence helped me move him off my life . I recommend you consult ETHICALHACKERS009 @ gmail.com OR CALL/TEXT +1(716) 318-5536 or whatsapp +14106350697 if you need access to your partner’s phone
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27.08.24 13:06
James889900
All you need is to hire an expert to help you accomplish that. If there’s any need to spy on your partner’s phone. From my experience I lacked evidence to confront my husband on my suspicion on his infidelity, until I came across ETHICALAHCKERS which many commend him of assisting them in their spying mission. So I contacted him and he provided me with access into his phone to view all text messages, call logs, WhatsApp messages and even her location. This evidence helped me move him off my life . I recommend you consult ETHICALHACKERS009 @ gmail.com OR CALL/TEXT +1(716) 318-5536 or whatsapp +14106350697 if you need access to your partner’s phone
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02.09.24 20:24
[email protected]
If You Need Hacker To Recover Your Bitcoin Contact Paradox Recovery Wizard Paradox Recovery Wizard successfully recovered $123,000 worth of Bitcoin for my husband, which he had lost due to a security breach. The process was efficient and secure, with their expert team guiding us through each step. They were able to trace and retrieve the lost cryptocurrency, restoring our peace of mind and financial stability. Their professionalism and expertise were instrumental in recovering our assets, and we are incredibly grateful for their service. Email: support@ paradoxrecoverywizard.com Email: paradox_recovery @cyberservices.com Wep: https://paradoxrecoverywizard.com/ WhatsApp: +39 351 222 3051.
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06.09.24 01:35
Celinagarcia
HOW TO RECOVER MONEY LOST IN BITCOIN/USDT TRADING OR TO CRYPTO INVESTMENT !! Hi all, friends and families. I am writing From Alberton Canada. Last year I tried to invest in cryptocurrency trading in 2023, but lost a significant amount of money to scammers. I was cheated of my money, but thank God, I was referred to Hack Recovery Wizard they are among the best bitcoin recovery specialists on the planet. they helped me get every penny I lost to the scammers back to me with their forensic techniques. and I would like to take this opportunity to advise everyone to avoid making cryptocurrency investments online. If you have already lost money on forex, cryptocurrency or Ponzi schemes, please contact [email protected] or WhatsApp: +1 (757) 237–1724 at once they can help you get back the crypto you lost to scammers. BEST WISHES. Celina Garcia.
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06.09.24 01:44
Celinagarcia
HOW TO RECOVER MONEY LOST IN BITCOIN/USDT TRADING OR TO CRYPTO INVESTMENT !! Hi all, friends and families. I am writing From Alberton Canada. Last year I tried to invest in cryptocurrency trading in 2023, but lost a significant amount of money to scammers. I was cheated of my money, but thank God, I was referred to Hack Recovery Wizard they are among the best bitcoin recovery specialists on the planet. they helped me get every penny I lost to the scammers back to me with their forensic techniques. and I would like to take this opportunity to advise everyone to avoid making cryptocurrency investments online. If you have already lost money on forex, cryptocurrency or Ponzi schemes, please contact [email protected] or WhatsApp: +1 (757) 237–1724 at once they can help you get back the crypto you lost to scammers. BEST WISHES. Celina Garcia.
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16.09.24 00:10
marcusaustin
Bitcoin Recovery Services: Restoring Lost Cryptocurrency If you've lost access to your cryptocurrency and unable to make a withdrawal, I highly recommend iBolt Cyber Hacker Bitcoin Recovery Services. Their team is skilled, professional, and efficient in recovering lost Bitcoin. They provide clear communication, maintain high security standards, and work quickly to resolve issues. Facing the stress of lost cryptocurrency, iBolt Cyber Hacker is a trusted service that will help you regain access to your funds securely and reliably. Highly recommended! Email: S u p p o r t @ ibolt cyber hack . com Cont/Whtp + 3. .9 .3. .5..0. .9. 2. 9. .0 .3. 1 .8. Website: h t t p s : / / ibolt cyber hack . com /
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16.09.24 00:11
marcusaustin
Bitcoin Recovery Services: Restoring Lost Cryptocurrency If you've lost access to your cryptocurrency and unable to make a withdrawal, I highly recommend iBolt Cyber Hacker Bitcoin Recovery Services. Their team is skilled, professional, and efficient in recovering lost Bitcoin. They provide clear communication, maintain high security standards, and work quickly to resolve issues. Facing the stress of lost cryptocurrency, iBolt Cyber Hacker is a trusted service that will help you regain access to your funds securely and reliably. Highly recommended! Email: S u p p o r t @ ibolt cyber hack . com Cont/Whtp + 3. .9 .3. .5..0. .9. 2. 9. .0 .3. 1 .8. Website: h t t p s : / / ibolt cyber hack . com /
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23.09.24 18:56
matthewshimself
At first, I was admittedly skeptical about Worldcoin (ref: https://worldcoin.org/blog/worldcoin/this-is-worldcoin-video-explainer-series), particularly around the use of biometric data and the WLD token as a reward mechanism for it. However, after following the project closer, I’ve come to appreciate the broader vision and see the value in the underlying tech behind it. The concept of Proof of Personhood (ref: https://worldcoin.org/blog/worldcoin/proof-of-personhood-what-it-is-why-its-needed) has definitely caught my attention, and does seem like a crucial step towards tackling growing issues like bots, deepfakes, and identity fraud. Sam Altman’s vision is nothing short of ambitious, but I do think he & Alex Blania have the chops to realize it as mainstay in the global economy.
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01.10.24 14:54
Sinewclaudia
I lost about $876k few months ago trading on a fake binary option investment websites. I didn't knew they were fake until I tried to withdraw. Immediately, I realized these guys were fake. I contacted Sinew Claudia world recovery, my friend who has such experience before and was able to recover them, recommended me to contact them. I'm a living testimony of a successful recovery now. You can contact the legitimate recovery company below for help and assistance. [email protected] [email protected] WhatsApp: 6262645164
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02.10.24 22:27
Emily Hunter
Can those who have fallen victim to fraud get their money back? Yes, you might be able to get back what was taken from you if you fell prey to a fraud from an unregulated investing platform or any other scam, but only if you report it to the relevant authorities. With the right plan and supporting documentation, you can get back what you've lost. Most likely, the individuals in control of these unregulated platforms would attempt to convince you that what happened to your money was a sad accident when, in fact, it was a highly skilled heist. You should be aware that there are resources out there to help you if you or someone you know has experienced one of these circumstances. Do a search using (deftrecoup (.) c o m). Do not let the perpetrators of this hoaxes get away with ruining you mentally and financially.
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18.10.24 09:34
freidatollerud
The growth of WIN44 in Brazil is very interesting! If you're looking for more options for online betting and casino games, I recommend checking out Casinos in Brazil. It's a reliable platform that offers a wide variety of games and provides a safe and enjoyable experience for users. It's worth checking out! https://win44.vip
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31.10.24 00:13
ytre89
Can those who have fallen victim to fraud get their money back? Yes, you might be able to get back what was taken from you if you fell prey to a fraud from an unregulated investing platform or any other scam, but only if you report it to the relevant authorities. With the right plan and supporting documentation, you can get back what you've lost. Most likely, the individuals in control of these unregulated platforms would attempt to convince you that what happened to your money was a sad accident when, in fact, it was a highly skilled heist. You should be aware that there are resources out there to help you if you or someone you know has experienced one of these circumstances. Do a search using (deftrecoup (.) c o m). Do not let the perpetrators of this hoaxes get away with ruining you mentally and financially.
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02.11.24 14:44
diannamendoza732
In the world of Bitcoin recovery, Pro Wizard Gilbert truly represents the gold standard. My experience with Gilbert revealed just how exceptional his methods are and why he stands out as the premier authority in this critical field. When I first encountered the complexities of Bitcoin recovery, I was daunted by the technical challenges and potential risks. Gilbert’s approach immediately distinguished itself through its precision and effectiveness. His methods are meticulously designed, combining cutting-edge techniques with an in-depth understanding of the Bitcoin ecosystem. He tackled the recovery process with a level of expertise and thoroughness that was both impressive and reassuring. What sets Gilbert’s methods apart is not just their technical sophistication but also their strategic depth. He conducts a comprehensive analysis of each case, tailoring his approach to address the unique aspects of the situation. This personalized strategy ensures that every recovery effort is optimized for success. Gilbert’s transparent communication throughout the process was invaluable, providing clarity and confidence during each stage of the recovery. The results I achieved with Pro Wizard Gilbert’s methods were remarkable. His gold standard approach not only recovered my Bitcoin but did so with an efficiency and reliability that exceeded my expectations. His deep knowledge, innovative techniques, and unwavering commitment make him the definitive expert in Bitcoin recovery. For anyone seeking a benchmark in Bitcoin recovery solutions, Pro Wizard Gilbert’s methods are the epitome of excellence. His ability to blend technical prowess with strategic insight truly sets him apart in the industry. Call: for help. You may get in touch with them at ; Email: (prowizardgilbertrecovery(@)engineer.com) Telegram ; https://t.me/Pro_Wizard_Gilbert_Recovery Homepage ; https://prowizardgilbertrecovery.info
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12.11.24 00:50
TERESA
Brigadia Tech Remikeable recovery has exhibited unparalleled strength in the realm of recovery. They stand out as the premier team to collaborate with if you encounter withdrawal difficulties from the platform where you’ve invested. Recently, I engaged with them to recover over a million dollars trapped in an investment platform I’d been involved with for months. I furnished their team with every detail of the investment, including accounts, names, and wallet addresses to which I sent the funds. This decision proved to be the best I’ve made, especially after realizing the company had scammed me. Brigadia Tech Remikeable recovery ensures exemplary service delivery and ensures the perpetrators face justice. They employ advanced techniques to ensure you regain access to your funds. Understandably, many individuals who have fallen victim to investment scams may still regret engaging in online services again due to the trauma of being scammed. However, I implore you to take action. Seek assistance from Brigadia Tech Remikeable Recovery Experts today and witness their remarkable capabilities. I am grateful that I resisted their enticements, and despite the time it took me to discover brigadia tech recovery, they ultimately fulfilled my primary objective. Without Brigadia Tech Recovery's intervention, I would have remained despondent and perplexed indefinitely. Also if you are looking for the best and safest investment company you can contact them, for wallet recovery, difficult withdrawal, etc. I am so happy to keep getting my daily BTC, all I do is keep 0.1 BTC in my mining wallet with the help of Brigadia Tech. They connected me to his mining stream and I earn 0.4 btc per day with this, my daily profit. I can get myself a new house and car. I can’t believe I have thousands of dollars in my bank account. Now you can get in. ([email protected]) Telegram +1 (323)-9 1 0 -1 6 0 5
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17.11.24 09:31
Vivianlocke223
Have You Fallen Victim to Cryptocurrency Fraud? If your Bitcoin or other cryptocurrencies were stolen due to scams or fraudulent activities, Free Crypto Recovery Fixed is here to help you recover what’s rightfully yours. As a leading recovery service, we specialize in restoring lost cryptocurrency and assisting victims of fraud — no matter how long ago the incident occurred. Our experienced team leverages cutting-edge tools and expertise to trace and recover stolen assets, ensuring swift and secure results. Don’t let scammers jeopardize your financial security. With Free Crypto Recovery Fixed, you’re putting your trust in a reliable and dedicated team that prioritizes recovering your assets and ensuring their future protection. Take the First Step Toward Recovery Today! 📞 Text/Call: +1 407 212 7493 ✉️ Email: [email protected] 🌐 Website: https://freecryptorecovery.net Let us help you regain control of your financial future — swiftly and securely.
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19.11.24 03:06
[email protected]
My entire existence fell apart when a malevolent hacker recently gained access to my online accounts. I felt violated and extremely uneasy after discovering that the digital platforms I depended on for communication, employment, and finances had been compromised. Regaining control and restoring my digital security was an overwhelming task in the immediate aftermath. To help me navigate the difficult process of recovering my accounts and getting my peace of mind back, TRUST GEEKS HACK EXPERT came into my life as a ray of hope. They immediately put their highly skilled professionals to work, thoroughly examining the vulnerability and methodically preventing unwanted access. They guided me through each stage soothingly, explaining what was occurring and why, so I never felt lost or alone. They communicated with service providers to restore my legitimate access while skillfully navigating the complex labyrinth of account recovery procedures. My digital footprint was cleaned and strengthened against future attacks thanks to their equally amazing ability to remove any remaining evidence of the hacker's presence. However, TRUST GEEKS HACK EXPERT actual worth went beyond its technical aspects. They offered constant emotional support during the ordeal, understanding my fragility and sense of violation. My tense nerves were calmed by their comforting presence and kind comments, which served as a reminder that I wasn't alone in this struggle. With their help, I was able to reestablish my sense of security and control, which enabled me to return my attention to the significant areas of my life that had been upended. Ultimately, TRUST GEEKS HACK EXPERT all-encompassing strategy not only recovered my online accounts but also my general peace of mind, which is a priceless result for which I am incredibly appreciative of their knowledge and kindness. Make the approach and send a message to TRUST GEEKS HACK EXPERT Via Web site <> www://trustgeekshackexpert.com/-- E>mail: Trustgeekshackexpert(At)fastservice..com -- TeleGram,<> Trustgeekshackexpert
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19.11.24 03:07
[email protected]
My entire existence fell apart when a malevolent hacker recently gained access to my online accounts. I felt violated and extremely uneasy after discovering that the digital platforms I depended on for communication, employment, and finances had been compromised. Regaining control and restoring my digital security was an overwhelming task in the immediate aftermath. To help me navigate the difficult process of recovering my accounts and getting my peace of mind back, TRUST GEEKS HACK EXPERT came into my life as a ray of hope. They immediately put their highly skilled professionals to work, thoroughly examining the vulnerability and methodically preventing unwanted access. They guided me through each stage soothingly, explaining what was occurring and why, so I never felt lost or alone. They communicated with service providers to restore my legitimate access while skillfully navigating the complex labyrinth of account recovery procedures. My digital footprint was cleaned and strengthened against future attacks thanks to their equally amazing ability to remove any remaining evidence of the hacker's presence. However, TRUST GEEKS HACK EXPERT actual worth went beyond its technical aspects. They offered constant emotional support during the ordeal, understanding my fragility and sense of violation. My tense nerves were calmed by their comforting presence and kind comments, which served as a reminder that I wasn't alone in this struggle. With their help, I was able to reestablish my sense of security and control, which enabled me to return my attention to the significant areas of my life that had been upended. Ultimately, TRUST GEEKS HACK EXPERT all-encompassing strategy not only recovered my online accounts but also my general peace of mind, which is a priceless result for which I am incredibly appreciative of their knowledge and kindness. Make the approach and send a message to TRUST GEEKS HACK EXPERT Via Web site <> www://trustgeekshackexpert.com/-- E>mail: Trustgeekshackexpert(At)fastservice..com -- TeleGram,<> Trustgeekshackexpert
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21.11.24 04:14
ronaldandre617
Being a parent is great until your toddler figures out how to use your devices. One afternoon, I left my phone unattended for just a few minutes rookie mistake of the century. I thought I’d take a quick break, but little did I know that my curious little genius was about to embark on a digital adventure. By the time I came back, I was greeted by two shocking revelations: my toddler had somehow managed to buy a $5 dinosaur toy online and, even more alarmingly, had locked me out of my cryptocurrency wallet holding a hefty $75,000. Yes, you heard that right a dinosaur toy was the least of my worries! At first, I laughed it off. I mean, what toddler doesn’t have a penchant for expensive toys? But then reality set in. I stared at my phone in disbelief, desperately trying to guess whatever random string of gibberish my toddler had typed as a new password. Was it “dinosaur”? Or perhaps “sippy cup”? I felt like I was in a bizarre game of Password Gone Wrong. Every attempt led to failure, and soon the laughter faded, replaced by sheer panic. I was in way over my head, and my heart raced as the countdown of time ticked away. That’s when I decided to take action and turned to Digital Tech Guard Recovery, hoping they could solve the mystery that was my toddler’s handiwork. I explained my predicament, half-expecting them to chuckle at my misfortune, but they were incredibly professional and empathetic. Their confidence put me at ease, and I knew I was in good hands. Contact With WhatsApp: +1 (443) 859 - 2886 Email digital tech guard . com Telegram: digital tech guard recovery . com website link :: https : // digital tech guard . com Their team took on the challenge like pros, employing their advanced techniques to unlock my wallet with a level of skill I can only describe as magical. As I paced around, anxiously waiting for updates, I imagined my toddler inadvertently locking away my life savings forever. But lo and behold, it didn’t take long for Digital Tech Guard Recovery to work their magic. Not only did they recover the $75,000, but they also gave me invaluable tips on securing my wallet better like not leaving it accessible to tiny fingers! Who knew parenting could lead to such dramatic situations? Crisis averted, and I learned my lesson: always keep my devices out of reach of little explorers. If you ever find yourself in a similar predicament whether it’s tech-savvy toddlers or other digital disasters don’t hesitate to reach out to Digital Tech Guard Recovery. They saved my funds and my sanity, proving that no challenge is too great, even when it involves a toddler’s mischievous fingers!
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21.11.24 08:02
Emily Hunter
If I hadn't found a review online and filed a complaint via email to support@deftrecoup. com , the people behind this unregulated scheme would have gotten away with leaving me in financial ruins. It was truly the most difficult period of my life.
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22.11.24 04:41
[email protected]
I never could have imagined the nightmare of losing access to my digital wallet. All of my cryptocurrency holdings were abruptly imprisoned, inaccessible, and appeared to be lost forever following a catastrophic hardware breakdown. Years of meticulous investment and careful saving were reduced to nothing more than strings of code that I could no longer control, and I could feel the dread and sorrow that swept through me at that very instant. Thankfully, during my worst moment, I came into (TRUST GEEKS HACK EXPERT), a professional service devoted to recovering lost or inaccessible digital data. With optimism, I went out to their team of skilled technologists, laying bare the full nature of my issue. What followed was a laborious, multi-step process that required an almost surgical level of digital forensics and Bitcoin skill. In order to create a thorough profile of my wallet's contents and activities, the (TRUST GEEKS HACK EXPERT) team first thoroughly examined the transaction history and metadata connected to it. Next, they implemented a series of advanced recovery techniques, using cutting-edge software tools to bypass the access barriers that had left me locked out. The entire process was shrouded in secrecy and discretion, with the (TRUST GEEKS HACK EXPERT) team working tirelessly to protect the confidentiality of my sensitive financial information. After what felt like an eternity of nervous anticipation, the day finally arrived when I received the triumphant notification – my wallet had been successfully restored, and all of my precious digital assets had been returned to my control. The sense of relief was indescribable, as I could finally breathe easy knowing that the fruits of my financial discipline had been safeguarded. While the experience of losing access to my wallet was undoubtedly traumatic, (TRUST GEEKS HACK EXPERT) intervention allowed me to emerge from the ordeal with my cryptocurrency holdings intact, and a renewed appreciation for the importance of proactive digital asset management. You can contact Them through EMAIL: [email protected] - TELEGRAM: TRUSTGEEKSHACKEXPERT
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22.11.24 15:26
cliftonhandyman
Your Lost Bitcoins Are Not Gone Forever? Enquire From iBolt Cyber Hacker iBolt Cyber Hacker is a cybersecurity service that specializes in Bitcoin and cryptocurrency recovery. Even if your Bitcoin is locked away in a scammer inaccessible wallet, they have the tools and expertise to retrieve it. Many people, including seasoned cryptocurrency investors, face the daunting possibility of never seeing their lost funds again. iBolt cyber hacker service is a potential lifeline in these situations. I understand the concerns many people might have about trusting a third-party service to recover their Bitcoin. iBolt Cyber Hacker takes security seriously, implementing encryption and stringent privacy protocols. I was assured that no sensitive data would be compromised during the recovery process. Furthermore, their reputation in the cryptocurrency community, based on positive feedback from previous clients, gave me confidence that I was in good hands. Whtp +39, 351..105, 3619 Em.ail: ibolt @ cyber- wizard. co m
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22.11.24 23:43
teresaborja
all thanks to Tech Cyber Force Recovery expert assistance. As a novice in cryptocurrency, I had been carefully accumulating a modest amount of Bitcoin, meticulously safeguarding my digital wallet and private keys. However, as the adage goes, the best-laid plans can often go awry, and that's precisely what happened to me. Due to a series of technical mishaps and human errors, I found myself locked out of my Bitcoin wallet, unable to access the fruits of my digital labors. Panic set in as I frantically searched for a solution, scouring the internet for any glimmer of hope. That's when I stumbled upon the Tech Cyber Force Recovery team, a group of seasoned cryptocurrency specialists who had built a reputation for their ability to recover lost or inaccessible digital assets. Skeptical at first, I reached out, desperate for a miracle. To my utter amazement, the Tech Cyber Force Recovery experts quickly assessed my situation and devised a meticulous plan of attack. Through their deep technical knowledge, unwavering determination, and a keen eye for detail, they were able to navigate the complex labyrinth of blockchain technology, ultimately recovering my entire Bitcoin portfolio. What had once seemed like a hopeless endeavor was now a reality, and I found myself once again in possession of my digital wealth, all thanks to the incredible efforts of the Tech Cyber Force Recovery team. This experience has not only restored my faith in the cryptocurrency ecosystem. Still, it has also instilled in me a profound appreciation for the critical role that expert recovery services can play in safeguarding one's digital assets. ENAIL < Tech cybers force recovery @ cyber services. com > WEBSITE < ht tps : // tech cyber force recovery. info > TEXT < +1. 561. 726. 3697 >
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24.11.24 02:21
[email protected]
I never could have imagined the nightmare of losing access to my digital wallet. All of my cryptocurrency holdings were abruptly imprisoned, inaccessible, and appeared to be lost forever following a catastrophic hardware breakdown. Years of meticulous investment and careful saving were reduced to nothing more than strings of code that I could no longer control, and I could feel the dread and sorrow that swept through me at that very instant. Thankfully, during my worst moment, I came into (TRUST GEEKS HACK EXPERT), a professional service devoted to recovering lost or inaccessible digital data. With optimism, I went out to their team of skilled technologists, laying bare the full nature of my issue. What followed was a laborious, multi-step process that required an almost surgical level of digital forensics and Bitcoin skill. In order to create a thorough profile of my wallet's contents and activities, the (TRUST GEEKS HACK EXPERT) team first thoroughly examined the transaction history and metadata connected to it. Next, they implemented a series of advanced recovery techniques, using cutting-edge software tools to bypass the access barriers that had left me locked out. The entire process was shrouded in secrecy and discretion, with the (TRUST GEEKS HACK EXPERT) team working tirelessly to protect the confidentiality of my sensitive financial information. After what felt like an eternity of nervous anticipation, the day finally arrived when I received the triumphant notification – my wallet had been successfully restored, and all of my precious digital assets had been returned to my control. The sense of relief was indescribable, as I could finally breathe easy knowing that the fruits of my financial discipline had been safeguarded. While the experience of losing access to my wallet was undoubtedly traumatic, (TRUST GEEKS HACK EXPERT) intervention allowed me to emerge from the ordeal with my cryptocurrency holdings intact, and a renewed appreciation for the importance of proactive digital asset management. You can contact Them through EMAIL: [email protected] - TELEGRAM: TRUSTGEEKSHACKEXPERT
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25.11.24 02:19
briankennedy
COMMENT ON I NEED A HACKER TO RECOVER MONEY FROM BINARY TRADING. HIRE FASTFUND RECOVERY
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25.11.24 02:20
briankennedy
After countless hours of research and desperate attempts to find a solution, I stumbled upon FASTFUND RECOVERY. It was like finding an oasis in the middle of a desert. Their website promised to help victims of scams reclaim what was rightfully theirs, and I instantly knew I had to give them a shot. Before diving headfirst into the recovery process, I wanted to make sure that FASTFUND RECOVERY was the real deal. So, I did my due diligence and looked into their expertise and reputation. To my relief, I found that they had an impeccable track record, successfully assisting countless individuals in recovering their lost funds. Their team consisted of experts in cybersecurity and financial fraud, armed with the knowledge and tools needed to tackle even the most intricate scams. With their reputation preceding them, I felt a renewed sense of hope. FASTFUND RECOVERY successfully came to my aid and got back the amount I lost to these scammers and for this, I am sending this article for clarification. The info of FASTFUND RECOVERY is email: Fastfundrecovery8 (@)Gmail (.) com. Web fastfundrecovery(.)com. (W/A 1 807/500/7554)
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26.11.24 21:59
[email protected]
In a world brimming with enticing investment opportunities, it is crucial to tread carefully. The rise of digital currencies has attracted many eager investors, but along with this excitement lurk deceitful characters ready to exploit the unsuspecting. I learned this lesson the hard way, and I want to share my story in the hopes that it can save someone from making the same mistakes I did. It all began innocently enough when I came across an engaging individual on Facebook. Lured in by promises of high returns in the cryptocurrency market, I felt the electric thrill of potential wealth coursing through me. Initial investments returned some profits, and that exhilarating taste of success fueled my ambition. Encouraged by a meager withdrawal, I decided to commit even more funds. This was the moment I let my guard down, blinded by greed. As time went on, the red flags started to multiply. The moment I tried to withdraw my earnings, a cascade of unreasonable fees appeared like a thick mist, obscuring the truth. “Just a little more,” they said, “Just until the next phase.” I watched my hard-earned money slip through my fingers as I scraped together every last cent to pay those relentless fees. My trust had become my downfall. In the end, I lost not just a significant amount of cash, but my peace of mind about $1.1 million vanished into the abyss of false promises and hollow guarantees. But despair birthed hope. After a cascade of letdowns, I enlisted the help of KAY-NINE CYBER SERVICES, a team that specializes in reclaiming lost funds from scams. Amazingly, they worked tirelessly to piece together what had been ripped away, providing me with honest guidance when I felt utterly defeated. Their expertise in navigating the treacherous waters of crypto recovery was a lifeline I desperately needed. To anyone reading this, please let my story serve as a warning. High returns often come wrapped in the guise of deception. Protect your investments, scrutinize every opportunity, and trust your instincts. Remember, the allure of quick riches can lead you straight to heartbreak, but with cautious determination and support, it is possible to begin healing from such devastating loss. Stay informed, stay vigilant, and may you choose your investment paths wisely. Email: kaynine @ cyberservices . com
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26.11.24 23:12
rickrobinson8
FAST SOLUTION FOR CYPTOCURRENCY RECOVERY SPARTAN TECH GROUP RETRIEVAL
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26.11.24 23:12
rickrobinson8
Although recovering from the terrible effects of investment fraud can seem like an impossible task, it is possible to regain financial stability and go on with the correct assistance and tools. In my own experience with Wizard Web Recovery, a specialized company that assisted me in navigating the difficulties of recouping my losses following my fall prey to a sophisticated online fraud, that was undoubtedly the case. My life money had disappeared in an instant, leaving me in a state of shock when I first contacted Spartan Tech Group Retrieval through this Email: spartantechretrieval (@) g r o u p m a i l .c o m The compassionate and knowledgeable team there quickly put my mind at ease, outlining a clear and comprehensive plan of action. They painstakingly examined every aspect of my case, using their broad business contacts and knowledge to track the movement of my pilfered money. They empowered me to make knowledgeable decisions regarding the rehabilitation process by keeping me updated and involved at every stage. But what I valued most was their unrelenting commitment and perseverance; they persisted in trying every option until a sizable amount of my lost money had been successfully restored. It was a long and arduous journey, filled with ups and downs, but having Spartan Tech Group Retrieval in my corner made all the difference. Thanks to their tireless efforts, I was eventually able to rebuild my financial foundation and reclaim a sense of security and control over my life. While the emotional scars of investment fraud may never fully heal, working with this remarkable organization played a crucial role in my ability to move forward and recover. For proper talks, contact on WhatsApp:+1 (971) 4 8 7 - 3 5 3 8 and Telegram:+1 (581) 2 8 6 - 8 0 9 2 Thank you for your time reading as it will be of help.
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27.11.24 00:39
[email protected]
Although recovering lost or inaccessible Bitcoin can be difficult and unpleasant, it is frequently possible to get back access to one's digital assets with the correct help and direction. Regarding the subject at hand, the examination of Trust Geeks Hack Expert Website www://trustgeekshackexpert.com/ assistance after an error emphasizes how important specialized services may be in negotiating the difficulties of Bitcoin recovery. These providers possess the technical expertise and resources necessary to assess the situation, identify the root cause of the issue, and devise a tailored solution to retrieve the lost funds. By delving deeper into the specifics of Trust Geeks Hack Expert approach, we can gain valuable insights into the nuances of this process. Perhaps they leveraged advanced blockchain analysis tools to trace the transaction history and pinpoint the location of the missing Bitcoins. Or they may have collaborated with the relevant parties, such as exchanges or wallet providers, to facilitate the recovery process. Equally important is the level of personalized support and communication that Trust Geeks Hack Expert likely provided, guiding the affected individual through each step of the recovery effort and offering reassurance during what can be an anxious and uncertain time. The success of their efforts, as evidenced by the positive outcome, underscores the importance of seeking out reputable and experienced service providers when faced with a Bitcoin-related mishap, as they possess the specialized knowledge and resources to navigate these challenges and restore access to one's digital assets. Email.. [email protected]
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27.11.24 09:10
Michal Novotny
The biggest issue with cryptocurrency is that it is unregulated, wh ich is why different people can come up with different fake stories all the time, and it is unfortunate that platforms like Facebook and others only care about the money they make from them through ads. I saw an ad on Facebook for Cointiger and fell into the scam, losing over $30,000. I reported it to Facebook, but they did nothing until I discovered deftrecoup . c o m from a crypto community; they retrieved approximately 95% of the total amount I lost.
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01.12.24 17:21
KollanderMurdasanu
REACH OUT TO THEM WhatsApp + 156 172 63 697 Telegram (@)Techcyberforc We were in quite a bit of distress. The thrill of our crypto investments, which had once sparked excitement in our lives, was slowly turning into anxiety when my husband pointed out unusual withdrawal issues. At first, we brushed it off as minor glitches, but the situation escalated when we found ourselves facing login re-validation requests that essentially locked us out of our crypto wallet—despite entering the correct credentials. Frustrated and anxious, we sought advice from a few friends, only to hit a wall of uncertainty. Turning to the vast expanse of the internet felt daunting, but in doing so, we stumbled upon TECH CYBER FORCE RECOVERY. I approached them with a mix of skepticism and hope; after all, my understanding of these technical matters was quite limited. Yet, from our very first interaction, it was clear that they were the experts we desperately needed. They walked us through the intricacies of the recovery process, patiently explaining each mechanism—even if some of it went over my head, their reassurance was calming. Our responsibility was simple: to provide the correct information to prove our ownership of the crypto account, and thankfully, we remained on point in our responses. in a timely fashion, TECH CYBER FORCE RECOVERY delivered on their promises, addressing all our withdrawal and access issues exactly when they said they would. The relief we felt was immense, and the integrity they displayed made me confident in fully recommending their services. If you ever find yourself in a similar predicament with your crypto investments, I wholeheartedly suggest reaching out to them. You can connect with TECH CYBER FORCE RECOVERY through their contact details for assistance and valuable guidance. Remember, hope is only a reach away!
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02.12.24 23:02
ytre89
Online crypto investment can seem like a promising opportunity, but it's crucial to recognize that there are no guarantees. My experience serves as a stark reminder of this reality. I was drawn in by the allure of high returns and the persuasive marketing tactics employed by various brokers. Their polished presentations and testimonials made it seem easy to profit from cryptocurrency trading. Everything appeared to be legitimate. I received enticing messages about the potential for substantial gains, and the brokers seemed knowledgeable and professional. Driven by excitement and the fear of missing out, I invested a significant amount of my savings. The promise of quick profits overshadowed the red flags I should have noticed. I trusted these brokers without conducting proper research, which was a major mistake. As time went on, I realized that the promised returns were nothing but illusions. My attempts to withdraw funds were met with endless excuses and delays. It became painfully clear that I had fallen victim. The reality hit hard: my hard-earned money was gone, I lost my peace of mind and sanity. In my desperation, I sought help from a company called DEFTRECOUP. That was the turning point for me as I had a good conversation and eventually filed a complaint via DEFTRECOUP COM. They were quite delicate and ensured I got out of the most difficult situation of my life in one piece.
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04.12.24 22:24
andreygagloev
When I first heard about Bitcoin back in 2018, I was skeptical. The idea of a decentralized, digital currency seemed too good to be true. But I was intrigued as I learned more about the technology behind it and its potential. I started small, investing just a few hundred dollars, dipping my toes into the cryptocurrency waters. At first, it was exhilarating to watch the value of my investment grow exponentially. I felt like I was part of the future, an early adopter of this revolutionary new asset. But that euphoria was short-lived. One day, I logged into my digital wallet only to find it empty - my Bitcoin had vanished without a trace. It turned out that the online exchange I had trusted had been hacked, and my funds were stolen. I was devastated, both financially and emotionally. All the potential I had seen in Bitcoin was tainted by the harsh reality that with decentralization came a lack of regulation and oversight. My hard-earned money was gone, lost to the ether of the digital world. This experience taught me a painful lesson about the price of trust in the uncharted territory of cryptocurrency. While the technology holds incredible promise, the risks can be catastrophic if you don't approach it with extreme caution. My Bitcoin investment gamble had failed, and I was left to pick up the pieces, wiser but poorer for having placed my faith in the wrong hands. My sincere appreciation goes to MUYERN TRUST HACKER. You are my hero in recovering my lost funds. Send a direct m a i l ( muyerntrusted ( @ ) mail-me ( . )c o m ) or message on whats app : + 1 ( 4-4-0 ) ( 3 -3 -5 ) ( 0-2-0-5 )
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12.12.24 00:35
amandagregory
HOW TO HIRE A HACKER TO RECOVER STOLEN BITCOIN WITH FASTFUND RECOVERY
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12.12.24 00:35
amandagregory
HOW TO HIRE A HACKER TO RECOVER STOLEN BITCOIN WITH FASTFUND RECOVERY... A few months ago, I made a huge mistake. I invested in what seemed like a legitimate crypto opportunity, only to find out I’d been scammed. I lost a significant amount of money, and the scam platform vanished overnight. I felt completely lost.I had heard of Fastfund Recovery and decided to reach out, even though I was skeptical. From the first conversation, they made me feel heard and understood. They explained the recovery process clearly and kept me updated every step of the way.Within weeks, Fastfund Recovery successfully to recovered my lost funds—something I honestly didn’t think was possible. Their team was professional, transparent, and genuinely caring. I can’t thank them enough for turning a nightmare into a hopeful outcome. If you’re in a similar situation, don’t hesitate to contact them. They truly deliver on their promises. Gmail::: fastfundrecovery8(@)gmail com .....Whatsapp ::: 1::807::::500::::7554
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19.12.24 17:07
rebeccabenjamin
USDT RECOVERY EXPERT REVIEWS DUNAMIS CYBER SOLUTION It's great to hear that you've found a way to recover your Bitcoin and achieve financial stability, but I urge you to be cautious with services like DUNAMIS CYBER SOLUTION Recovery." While it can be tempting to turn to these companies when you’re desperate to recover lost funds, many such services are scams, designed to exploit those in vulnerable situations. Always research thoroughly before engaging with any recovery service. In the world of cryptocurrency, security is crucial. To protect your assets, use strong passwords, enable two-factor authentication, and consider using cold wallets (offline storage) for long-term storage. If you do seek professional help, make sure the company is reputable and has positive, verifiable reviews from trusted sources. While it’s good that you found a solution, it’s also important to be aware of potential scams targeting cryptocurrency users. Stay informed about security practices, and make sure you take every step to safeguard your investments. If you need help with crypto security tips or to find trustworthy resources, feel free to ask! [email protected] +13433030545 [email protected]
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24.12.24 08:33
dddana
Отличная подборка сервисов! Хотелось бы дополнить список рекомендацией: нажмите сюда - https://airbrush.com/background-remover. Этот инструмент отлично справляется с удалением фона, сохраняя при этом высокое качество изображения. Очень удобен для быстрого редактирования фото. Было бы здорово увидеть его в вашей статье!
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27.12.24 00:21
swiftdream
I lost about $475,000.00 USD to a fake cryptocurrency trading platform a few weeks back after I got lured into the trading platform with the intent of earning a 15% profit daily trading on the platform. It was a hell of a time for me as I could hardly pay my bills and got me ruined financially. I had to confide in a close friend of mine who then introduced me to this crypto recovery team with the best recovery SWIFTDREAM i contacted them and they were able to completely recover my stolen digital assets with ease. Their service was superb, and my problems were solved in swift action, It only took them 48 hours to investigate and track down those scammers and my funds were returned to me. I strongly recommend this team to anyone going through a similar situation with their investment or fund theft to look up this team for the best appropriate solution to avoid losing huge funds to these scammers. Send complaint to Email: info [email protected]
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31.12.24 04:53
Annette_Phillips
There are a lot of untrue recommendations and it's hard to tell who is legit. If you have lost crypto to scam expresshacker99@gmailcom is the best option I can bet on that cause I have seen lot of recommendations about them and I'm a witness on their capabilities. They will surely help out. Took me long to find them. The wonderful part is no upfront fee till crypto is recover successfully that's how genuine they are.
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04.01.25 04:56
florencestella
THE BEST CERTIFIED CRYPTOCURRENCY RECOVERY EXPERT DUNAMIS CYBER SOLUTION
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04.01.25 04:57
florencestella
THE BEST CERTIFIED CRYPTOCURRENCY RECOVERY EXPERT DUNAMIS CYBER SOLUTION It sounds like you went through a very frustrating experience with Cointrack, where your access to your own funds was unjustly restricted for months without clear communication or a solution. The extended periods of account freezes, lack of transparency, and vague customer support responses would make anyone anxious. It’s understandable that you suspected the issue could be related to your login activity, but it’s surprising that something as minor as using the same Wi-Fi network could trigger such severe restrictions. I’m glad to hear that DUNAMIS CYBER SOLUTION Recovery was able to help you get your account unlocked and resolve the issue. It’s unfortunate that you had to seek third-party assistance, but it’s a relief that the situation was eventually addressed. If you plan on using any platforms like this again, you might want to be extra cautious, especially when dealing with sensitive financial matters. And if you ever need to share your experience to help others avoid similar issues, feel free to reach out. It might be helpful for others to know about both the pitfalls and the eventual resolution through services like DUNAMIS CYBER SOLUTION Recovery. [email protected] +13433030545 [email protected]
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06.01.25 19:09
michaeljordan15
We now live in a world where most business transactions are conducted through Bitcoin and cryptocurrency. With the rapid growth of digital currencies, everyone seems eager to get involved in Bitcoin and cryptocurrency investments. This surge in interest has unfortunately led to the rise of many fraudulent platforms designed to exploit unsuspecting individuals. People are often promised massive profits, only to lose huge sums of money when they realize the platform they invested in was a scam. contact with WhatsApp: +1 (443) 859 - 2886 Email @ digitaltechguard.com Telegram: digitaltechguardrecovery.com website link:: https://digitaltechguard.com This was exactly what happened to me five months ago. I was excited about the opportunity to invest in Bitcoin, hoping to earn a steady return of 20%. I found a platform that seemed legitimate and made my investment, eagerly anticipating the day when I would be able to withdraw my earnings. When the withdrawal day arrived, however, I encountered an issue. My bank account was not credited, despite seeing my balance and the supposed profits in my account on the platform. At first, I assumed it was just a technical glitch. I thought, "Maybe it’s a delay in the system, and everything will be sorted out soon." However, when I tried to contact customer support, the line was either disconnected or completely unresponsive. My doubts started to grow, but I wanted to give them the benefit of the doubt and waited throughout the day to see if the situation would resolve itself. But by the end of the day, I realized something was terribly wrong. I had been swindled, and my hard-earned money was gone. The realization hit me hard. I had fallen victim to one of the many fraudulent Bitcoin platforms that promise high returns and disappear once they have your money. I knew I had to act quickly to try and recover what I had lost. I started searching online for any possible solutions, reading reviews and recommendations from others who had faced similar situations. That’s when I came across many positive reviews about Digital Tech Guard Recovery. After reading about their success stories, I decided to reach out and use their services. I can honestly say that Digital Tech Guard Recovery exceeded all my expectations. Their team was professional, efficient, and transparent throughout the process. Within a short time, they helped me recover a significant portion of my lost funds, which I thought was impossible. I am incredibly grateful to Digital Tech Guard Recovery for their dedication and expertise in helping me get my money back. If you’ve been scammed like I was, don’t lose hope. There are solutions, and Digital Tech Guard Recovery is truly one of the best. Thank you, Digital Tech Guard Recovery! You guys are the best. Good luck to everyone trying to navigate this challenging space. Stay safe.
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18.01.25 12:41
michaeldavenport218
I was recently scammed out of $53,000 by a fraudulent Bitcoin investment scheme, which added significant stress to my already difficult health issues, as I was also facing cancer surgery expenses. Desperate to recover my funds, I spent hours researching and consulting other victims, which led me to discover the excellent reputation of Capital Crypto Recover, I came across a Google post It was only after spending many hours researching and asking other victims for advice that I discovered Capital Crypto Recovery’s stellar reputation. I decided to contact them because of their successful recovery record and encouraging client testimonials. I had no idea that this would be the pivotal moment in my fight against cryptocurrency theft. Thanks to their expert team, I was able to recover my lost cryptocurrency back. The process was intricate, but Capital Crypto Recovery's commitment to utilizing the latest technology ensured a successful outcome. I highly recommend their services to anyone who has fallen victim to cryptocurrency fraud. For assistance, contact [email protected] Capital Crypto Recover on Telegram OR Call Number +1 (336)390-6684 via email: [email protected]
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18.01.25 12:41
michaeldavenport218
I was recently scammed out of $53,000 by a fraudulent Bitcoin investment scheme, which added significant stress to my already difficult health issues, as I was also facing cancer surgery expenses. Desperate to recover my funds, I spent hours researching and consulting other victims, which led me to discover the excellent reputation of Capital Crypto Recover, I came across a Google post It was only after spending many hours researching and asking other victims for advice that I discovered Capital Crypto Recovery’s stellar reputation. I decided to contact them because of their successful recovery record and encouraging client testimonials. I had no idea that this would be the pivotal moment in my fight against cryptocurrency theft. Thanks to their expert team, I was able to recover my lost cryptocurrency back. The process was intricate, but Capital Crypto Recovery's commitment to utilizing the latest technology ensured a successful outcome. I highly recommend their services to anyone who has fallen victim to cryptocurrency fraud. For assistance, contact [email protected] Capital Crypto Recover on Telegram OR Call Number +1 (336)390-6684 via email: [email protected]
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20.01.25 15:39
patricialovick86
How To Recover Your Bitcoin Without Falling Victim To Scams: A Testimony Experience With Capital Crypto Recover Services, Contact Telegram: @Capitalcryptorecover Dear Everyone, I would like to take a moment to share my positive experience with Capital Crypto Recover Services. Initially, I was unsure if it would be possible to recover my stolen bitcoins. However, with their expertise and professionalism, I was able to fully recover my funds. Unfortunately, many individuals fall victim to scams in the cryptocurrency space, especially those involving fraudulent investment platforms. However, I advise caution, as not all recovery services are legitimate. I personally lost $273,000 worth of Bitcoin from my Binance account due to a deceptive platform. If you have suffered a similar loss, you may be considering crypto recovery, The Capital Crypto Recover is the most knowledgeable and effective Capital Crypto Recovery Services assisted me in recovering my stolen funds within 24 hours, after getting access to my wallet. Their service was not only prompt but also highly professional and effective, and many recovery services may not be trustworthy. Therefore, I highly recommend Capital Crypto Recover to you. i do always research and see reviews about their service, For assistance finding your misplaced cryptocurrency, get in touch with them, They do their jobs quickly and excellently, Stay safe and vigilant in the crypto world. You can reach them via email at [email protected] OR Call/Text Number +1 (336)390-6684 his contact: [email protected]
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22.01.25 21:43
DoraJaimes23
Recovery expert. I lost my bitcoin to fake blockchain impostors on Facebook, they contacted me as blockchain official support and i fell stupidly for their mischievous act, this made them gain access into my blockchain wallet whereby 7.0938 btc was stolen from my wallet in total .I was almost in a comma and dumbfounded because this was all my savings i relied on . Then I made a research online and found a recovery expert , with the contact address- { RECOVERYHACKER101 (@) GMAIL . COM }... I wrote directly to the specialist explaining my loss. Hence, he helped me recover a significant part of my investment just after 2 days he helped me launch the recovery program , and the culprits were identified as well , all thanks to his expertise . I hope I have been able to help someone as well . Reach out to the recovery specialist to recover you lost funds from any form of online scam Thanks
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23.01.25 02:36
[email protected]
After falling victim to a fraudulent Bitcoin mining scam, I found myself in a desperate situation. I had invested $50,000 into a cloud mining website called Miningpool, which turned out to be a complete scam. For months, I tried reaching out to the company, but I was unable to access my funds, and I quickly realized I had been taken for a ride. In my search for help, I came across TrustGeeks Hack Expert, a service that claimed to help people recover lost funds from crypto scams. Though skeptical at first, I decided to give them a try. Here’s my experience with their service.When I initially contacted TrustGeeks Hack Expert Email.. Trustgeekshackexpert{At}fastservice{Dot}com , I was understandably hesitant. Like many others, I had been tricked into believing my Bitcoin investments were legitimate, only to discover they were locked in a non-spendable wallet with no way of accessing them. However, after sharing my story and details about the scam, the team assured me they had handled similar cases and had the expertise to help. They requested basic information about my investment and began their investigation immediately. The recovery process was nothing short of professional. Unlike many other services that promise quick fixes but fail to deliver, TrustGeeks Hack Expert kept me informed at every stage. They regularly updated me on their progress and were completely transparent about the challenges they faced. There were moments when I wondered if the process would work, but the team’s professionalism and reassurance gave me hope. They were honest about the time it would take and did not make any unrealistic promises, which I truly appreciated. After several weeks of work, TrustGeeks Hack Expert successfully recovered not just my $50,000 investment, but also the so-called profits that had been locked away in the scam's non-spendable wallet. This was a huge relief, as I had resigned myself to the idea that I had lost everything. The entire recovery process was discreet and handled with the utmost care, ensuring that the scam company remained unaware of the recovery efforts, which helped prevent further complications. TeleGram iD. Trustgeekshackexpert & What's A p p +1 7 1 9 4 9 2 2 6 9 3
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23.01.25 02:37
[email protected]
After falling victim to a fraudulent Bitcoin mining scam, I found myself in a desperate situation. I had invested $50,000 into a cloud mining website called Miningpool, which turned out to be a complete scam. For months, I tried reaching out to the company, but I was unable to access my funds, and I quickly realized I had been taken for a ride. In my search for help, I came across TrustGeeks Hack Expert, a service that claimed to help people recover lost funds from crypto scams. Though skeptical at first, I decided to give them a try. Here’s my experience with their service.When I initially contacted TrustGeeks Hack Expert Email.. Trustgeekshackexpert{At}fastservice{Dot}com , I was understandably hesitant. Like many others, I had been tricked into believing my Bitcoin investments were legitimate, only to discover they were locked in a non-spendable wallet with no way of accessing them. However, after sharing my story and details about the scam, the team assured me they had handled similar cases and had the expertise to help. They requested basic information about my investment and began their investigation immediately. The recovery process was nothing short of professional. Unlike many other services that promise quick fixes but fail to deliver, TrustGeeks Hack Expert kept me informed at every stage. They regularly updated me on their progress and were completely transparent about the challenges they faced. There were moments when I wondered if the process would work, but the team’s professionalism and reassurance gave me hope. They were honest about the time it would take and did not make any unrealistic promises, which I truly appreciated. After several weeks of work, TrustGeeks Hack Expert successfully recovered not just my $50,000 investment, but also the so-called profits that had been locked away in the scam's non-spendable wallet. This was a huge relief, as I had resigned myself to the idea that I had lost everything. The entire recovery process was discreet and handled with the utmost care, ensuring that the scam company remained unaware of the recovery efforts, which helped prevent further complications. TeleGram iD. Trustgeekshackexpert & What's A p p +1 7 1 9 4 9 2 2 6 9 3
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23.01.25 14:20
nellymargaret
DUNAM CYBER SOLUTION BTC-ETH RECOVERY EXPERT
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23.01.25 14:20
nellymargaret
DUNAM CYBER SOLUTION BTC-ETH RECOVERY EXPERT I had tried to secure my Bitcoin wallet, maybe a bit too aggressively, enabling every security feature imaginable: two-factor authentication, biometric verification, intricate passwords-the whole shebang. I wanted to make it impossible for anybody to get to my money. I tried to make this impregnable fortress of security and ended up locking myself out of my wallet with $700,000 in Bitcoin. It wasn't until I tried to access my wallet that I realized the trap I had set for myself. I was greeted with an endless series of security checks-passwords, codes, facial recognition, and more. I could remember parts of my multi-layered security setup but not enough to actually get in. In fact, my money was behind this digital fortress, and the more I tried to fix it, the worse it seemed to get. I kept tripping over my own layers of protection, unable to find a way back in. Panic quickly set in when I realized I had made it almost impossible for myself to access my own money. That is when I called DUNAMIS CYBER SOLUTION From that very first call, they reassured me that I wasn't the first person to make this kind of mistake and certainly wouldn't be the last. They listened attentively to my explanation and got to work straight away. Their team methodically began to untangle my overly complicated setup. Patience and expertise managed to crack each layer of security step by step until they had restored access to my wallet. [email protected] +13433030545 [email protected]
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26.01.25 03:54
[email protected]
Losing access to my crypto wallet account was one of the most stressful experiences ever. After spending countless hours building up my portfolio, I suddenly found myself locked out of my account without access. To make matters worse, the email address I had linked to my wallet was no longer active. When I tried reaching out, I received an error message stating that the domain was no longer in use, leaving me in complete confusion and panic. It was as though everything I had worked so hard for was gone, and I had no idea how to get it back. The hardest part wasn’t just the loss of access it was the feeling of helplessness. Crypto transactions are often irreversible, and since my wallet held significant investments, the thought that my hard-earned money could be lost forever was incredibly disheartening. I spent hours scouring forums and searching for ways to recover my funds, but most of the advice seemed either too vague or too complicated to be of any real help. With no support from the wallet provider and my email account out of reach, I was left feeling like I had no way to fix the situation.That’s when I found out about Trust Geeks Hack Expert . I was hesitant at first, but after reading about their expertise in recovering lost crypto wallets, I decided to give them a try. I reached out to their team, and from the very beginning, they were professional, understanding, and empathetic to my situation. They quickly assured me that there was a way to recover my wallet, and they got to work immediately.Thanks to Trust Geeks Hack Expert , my wallet and funds were recovered, and I couldn’t be more grateful. The process wasn’t easy, but their team guided me through each step with precision and care. The sense of relief I felt when I regained access to my crypto wallet and saw my funds safely back in place was indescribable. If you find yourself in a similar situation, I highly recommend reaching out to Trust Geeks Hack Expert. contact Them through EMAIL: [email protected] + WEBSITE. HTTPS://TRUSTGEEKSHACKEXPERT.COM + TELE GRAM: TRUSTGEEKSHACKEXPERT
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28.01.25 21:48
[email protected]
It’s unfortunate that many people have become victims of scams, and some are facing challenges accessing their Bitcoin wallets. However, there's excellent news! With Chris Wang, you can count on top-notch service that guarantees results in hacking. We have successfully helped both individuals and organizations recover lost files, passwords, funds, and more. If you need assistance, don’t hesitate—check out recoverypro247 on Google Mail! What specific methods does Chris Wang use to recover lost funds and passwords? Are there any guarantees regarding the success rate of the recovery services offered? What are the initial steps to begin the recovery process with recoverypro247? this things i tend to ask
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02.02.25 20:53
Michael9090
I lost over $155,000 in an investment trading company last year; I was down because the company refused to let me make withdrawals and kept asking for more money…. My friend in the military introduced me to a recovery agent Crypto Assets Recovery with the email address [email protected] and he’s been really helpful, he made a successful recovery of 95% of my investment in less than 24 hours, I’m so grateful to him. If you are a victim of a binary scam and need to get your money back, please don’t hesitate to contact Crypto Assets Recovery in any of the information below. EMAIL: [email protected] WHATSAPP NUMBER : +18125892766
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05.02.25 00:04
Jannetjeersten
TECH CYBER FORCE RECOVERY quickly took action, filing my case and working tirelessly on my behalf. Within just four days, I received the surprising news that my 40,000 CAD had been successfully refunded and deposited back into my bank account. I was overjoyed and relieved to see the money returned, especially after the stressful experience. Thanks to TECH CYBER FORCE RECOVERY’s professionalism and dedication, I was able to recover my funds. This experience taught me an important lesson about being cautious with online investments and the importance of seeking expert help when dealing with scams. I am truly grateful to EMAIL: support(@)techcyberforcerecovery(.)com OR WhatsApp: +.1.5.6.1.7.2.6.3.6.9.7 for their assistance, which allowed me to reclaim my money and end the holiday season on a much brighter note.
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06.02.25 19:42
Marta Golomb
My name is Marta, and I’m sharing my experience in the hope that it might help others avoid a similar scam. A few weeks ago, I received an email that appeared to be from the "Department of Health and Human Services (DHS)." It claimed I was eligible for a $72,000 grant debit card, which seemed like an incredible opportunity. At first, I was skeptical, but the email looked so professional and convincing that I thought it might be real. The email instructed me to click on a link to claim the grant, and unfortunately, I followed through. I filled out some personal details, and then, unexpectedly, I was told I needed to pay a "processing fee" to finalize the grant. I was hesitant, but the urgency of the message pushed me to make the payment, believing it was a necessary step to receive the funds. Once the payment was made, things quickly went downhill. The website became unreachable, and I couldn’t get in touch with anyone from the supposed DHS. It soon became clear that I had been scammed. The email, which seemed so legitimate, had been a clever trick to steal my money.Devastated and unsure of what to do, I began searching for ways to recover my lost funds. That’s when I found Tech Cyber Force Recovery, a team of experts who specialize in tracing stolen money and assisting victims of online fraud. They were incredibly reassuring and quickly got to work on my case. After several days of investigation, they managed to track down the scammers and recover my funds. I can’t express how grateful I am for their help. Without Tech Cyber Force Recovery, I don’t know what I would have done. This experience has taught me a valuable lesson: online scams are more common than I realized, and the scammers behind them are incredibly skilled. They prey on people’s trust, making it easy to fall for their tricks. HOW CAN I RECOVER MY LOST BTC,USDT =Telegram= +1 561-726-36-97 =WhatsApp= +1 561-726-36-97
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08.02.25 05:45
[email protected]
I'm incredibly grateful that I did enough research to recover my stolen cryptocurrency. When I first fell victim to a scam, I felt hopeless and lost, unsure if I'd ever see my funds again. A few months ago, I was approached by someone on Telegram who claimed to have a lucrative investment opportunity in cryptocurrencies. They promised huge returns and played on my emotions, making it seem like a can't-miss chance. I was so eager to make my money grow that I didn't fully vet the situation, and unfortunately, I ended up falling for the scam. They guided me to invest a significant amount of money, and soon after, I realized I had been duped. The scammers blocked me, and my funds were gone. I felt devastated. All of my savings had been wiped out in what seemed like an instant, and the feeling of being taken advantage of was crushing. I spent days researching how to recover my stolen cryptocurrency but found the process to be overwhelming and complicated. I was starting to lose hope when I came across Trust Geeks Hack Expert. At first, I was skeptical about reaching out to a cryptocurrency recovery company, but after reading testimonials and researching their reputation, I decided to give them a try. I contacted Trust Geeks Hack Expert Website: www://trustgeekshackexpert.com/, and I was immediately reassured by their professionalism and expertise. They took the time to listen to my situation, and they were honest about what could and could not be done. What stood out to me was their deep understanding of cryptocurrency fraud and the recovery process. They were able to track down the scammers and initiate the recovery of my stolen funds, step by step. Thanks to Trust Geeks Hack Expert, I was able to get back a significant portion of the cryptocurrency I had lost. Their team was responsive, transparent, and diligent in their efforts. I was kept informed throughout the entire process, and they made sure I felt supported every step of the way. I truly can't thank them enough for their dedication and for restoring my faith in the possibility of recovery after such a devastating loss. I will definitely recommend Trust Geeks Hack Expert to anyone who has fallen victim to a cryptocurrency scam. TeleGram: Trustgeekshackexpert & what's A p p +1 7 1 9 4 9 2 2 6 9 3
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08.02.25 05:46
[email protected]
I'm incredibly grateful that I did enough research to recover my stolen cryptocurrency. When I first fell victim to a scam, I felt hopeless and lost, unsure if I'd ever see my funds again. A few months ago, I was approached by someone on Telegram who claimed to have a lucrative investment opportunity in cryptocurrencies. They promised huge returns and played on my emotions, making it seem like a can't-miss chance. I was so eager to make my money grow that I didn't fully vet the situation, and unfortunately, I ended up falling for the scam. They guided me to invest a significant amount of money, and soon after, I realized I had been duped. The scammers blocked me, and my funds were gone. I felt devastated. All of my savings had been wiped out in what seemed like an instant, and the feeling of being taken advantage of was crushing. I spent days researching how to recover my stolen cryptocurrency but found the process to be overwhelming and complicated. I was starting to lose hope when I came across Trust Geeks Hack Expert. At first, I was skeptical about reaching out to a cryptocurrency recovery company, but after reading testimonials and researching their reputation, I decided to give them a try. I contacted Trust Geeks Hack Expert Website: www://trustgeekshackexpert.com/, and I was immediately reassured by their professionalism and expertise. They took the time to listen to my situation, and they were honest about what could and could not be done. What stood out to me was their deep understanding of cryptocurrency fraud and the recovery process. They were able to track down the scammers and initiate the recovery of my stolen funds, step by step. Thanks to Trust Geeks Hack Expert, I was able to get back a significant portion of the cryptocurrency I had lost. Their team was responsive, transparent, and diligent in their efforts. I was kept informed throughout the entire process, and they made sure I felt supported every step of the way. I truly can't thank them enough for their dedication and for restoring my faith in the possibility of recovery after such a devastating loss. I will definitely recommend Trust Geeks Hack Expert to anyone who has fallen victim to a cryptocurrency scam. TeleGram: Trustgeekshackexpert & what's A p p +1 7 1 9 4 9 2 2 6 9 3
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10.02.25 21:22
sulabhakuchchal
W.W.W.techcyberforcerecovery.com MAIL. [email protected] My name is sulabha kuchchal, and I’m from Mumbai. A few months ago, I faced a nightmare scenario that many in the crypto world fear: I lost access to my $60,000 wallet after a malware attack. The hacker gained control of my private keys, and I was unable to access my funds. Panic set in immediately as I realized the magnitude of the situation. Like anyone in my shoes, I felt completely helpless. But luckily, a friend recommended TECH CYBER FORCE RECOVERY, and it turned out to be the best advice I could have gotten. From the moment I reached out to TECH CYBER FORCE RECOVERY, I felt a sense of relief.
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04:24
heyemiliohutchinson
I invested substantially in Bitcoin, believing it would secure my future. For a while, things seemed to be going well. The market fluctuated, but I was confident my investment would pay off. But catastrophe struck without warning. I lost access to my Bitcoin holdings as a result of several technical issues and inadequate security measures. Every coin in my wallet suddenly disappeared, leaving me with an overpowering sense of grief. The emotional impact of this loss was far greater than I had imagined. I spiraled into despair, feeling as though my dreams of financial independence were crushed. I was on the verge of giving up when I came across Assets_Recovery_Crusader. Being willing to give them a chance, I had nothing left to lose. They listened to my narrative and took the time to comprehend the particulars of my circumstance, rather than treating me like a case number. They worked diligently, using their advanced recovery techniques and deep understanding of blockchain technology to track down my lost Bitcoin. Assets_Recovery_Crusader rebuilt my trust in the bitcoin space. The financial impact had a significant emotional toll, but I was able to get past it thanks to Assets_Recovery_Crusader’s proficiency and persistence. For proper talks, reach out to them via TELEGRAM : Assets_Recovery_Crusader EMAIL: [email protected]
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