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Ускорение и облегчение моделей для поддержания диалога виртуальных ассистентов Салют

В распоряжении SberDevices — огромные core-модели, построенные на всем известной архитектуре Transformer. Обучение такой модели может занимать очень много времени, а Inference — требует большого количества памяти компьютера. Расскажу, как при таких вводных мы обучаем core-модели и какие хаки мы используем, чтобы их облегчить и ускорить. Речь пойдёт о ML с позиции пайплайнов и продакшена виртуального ассистента Салют.

Привет, Хабр! Меня зовут Александр Абрамов и я ML Lead продукта в SberDevices. Эта статья — про обучение core-моделей retrieval-based диалоговых систем, поговорим про хинты для ускорения обучения и сходимости, также затрону тему общей схемы inference и оптимизации её компонентов.

Статья создана на основе моего доклада для конференции Highload.

Архитектура в голосовом ассистенте Салют решает множество задач: распознавание речи, предобработка текста, определение именованных сущностей, классификация намерения, аннотирование, исполнение навыка.

Всё это нужно, чтобы вести осознанный, интересный, эмпатичный, эмоциональный диалог. При этом на задержку даётся не больше одной секунды, то есть все эти задачи должны последовательно исполниться за 1 секунду и никак не более.

Как в Салют устроены core-модели

Core-модели в Салют строятся на больших трансформерных архитектурах.

Вначале у нас был BERT Large трансформер, занимающий в памяти GPU около 2 гигабайт. И это без учёта дообучения, то есть размер этот постоянно увеличивался. Ведь обучали мы его на огромных наборах данных — порядка миллионов различных диалогов, огромное количество специальной пост-тег разметки именованных сущностей, намерений, различной информации, определение тональности текста. Всё это помещалось для обучения в наш пайплайн с BERT Large.

Чтобы эта модель эффективно представляла наш текст в виде вектора, мы использовали Metric-Learning.

SBERT и Multi-GPU Learning

Чтобы задачи влезли в наш пайплайн обучения модели, мы использовали HOROVOD multi-GPU learning. HOROVOD — библиотека, позволяющая обучать модель как на TensorFlow, так и на PyTorch из коробки на нескольких GPU.

Мы используем его так:

Все данные шардируются, батчируются, раскидываются на несколько GPU-нод, которые параллельно учатся на одной и той же архитектуре. На старте каждая архитектура инициализируется рандомно, независимо друг от друга, и в конце каждой эпохи обучения веса “суммируются” за счёт обмена градиентами между GPU. По сути, мы используем DataParallel подход multiGPU-leaning. Так мы создаём улучшенную модель из весов моделей, которые мы раскидывали на GPU при помощи HOROVOD. В результате получили не простой BERT, а именно SBERT-multitask.

SBERT-multitask эффективно представляет поисковые запросы. А кроме этих запросов мы учим его вести диалоги, определять именованные сущности и так далее. Также есть несколько дополнительных тасок, поэтому нам требуется размещать в памяти GPU всю эту информацию.

Облегчаем core NLU: дистилляция и сжатие

Мы используем не только распараллеливания вычислений, но и способы облегчения модели при помощи дистилляции и сжатия. Это когда мы от сильной модели учителя передаём знания более слабой модели ученику, с минимальными потерями качества.

В данном случае мы используем в качестве одного из примеров LABSE-модель. Это тоже одна из последних известных моделей с эффективным представлением sentence-эмбеддингов. Используем дистилляцию эмбеддингов нашей SBERT модели, которую мы так масштабно обучили, к LABSE-модели. Это позволяет уменьшить размерность поискового индекса примерно в 3,5 раза. Делаем мы это за счёт пожимающего shift-слоя, который позволяет вместо размерности вектора 1024 иметь 768, а в конечном счете мы дошли до 300 от мерного представления. К тому же при дистилляции идёт наследование свойств — это добавляет 4% к качеству релевантности и 10% к скорости поиска. А поисковый индекс, используемый нами из векторов, с пониженной размерностью, весит в памяти всего лишь 400 MB.

Мы должны подумать не только о том, чтобы наша модель быстро работала, была сжатой, занимала меньше памяти, она ещё должна сохранять адекватность разговора. Для этого нам нужно продумать её устойчивость к атакам.

Ускорение и робастное обучение: core NLU. Adversarial Attack

Чтобы модель была устойчива к атакам, мы сделали два фреймворка. Первый — simple_aug, который использует все возможные лингвистические замены наших символов во входной фразе на ошибочные символы, так у нас появляется match ошибок. При этом мы дополнительно используем RuTextFooler, который заменяет наши фразы не на уровне символов, а полностью — на похожие по написанию, но разные по смыслу. Таким образом, наша устойчивость увеличивается. В настоящее время оба этих модуля являются частями нашей библиотеки augmentex.

Такая устойчивость не только повышает качество модели, то есть её релевантность и разнообразие ответов, но и влияет на скорость сходимости. То есть вы получаете лучшую модель при обучении не за 10 эпох, а за 5 или за 7. Это на 5-10% увеличивает скорость обучения конечной модели.

Семплинг обучения core NLU

Так как модель у нас большая и мы используем там много тасок, то в один батч для каждой таски помещается не больше 24-32 сэмплов. Если мы умножим это на 10 задач, то в самом большом размере будет 320 значений.

Если мы используем dgx v100 размером в 32 GB, то он едва ли это вместит, то есть батч будет маленький. Но мы знаем, что чем больше батч, тем лучше качество у трансформеров.

Исправить потенциальное падение оценки качества от размера батча можно с помощью Metric Learning подхода. У нас есть вопрос от пользователя, релевантный ответ и неправильный ответ на этот вопрос. Такими «тройками» мы кормим модель. Раньше использовали только уникальные тройки (вопрос + положительная пара или отрицательная пара), но затем начали использовать FullBatching.

Ускоряем обучение: core NLU. FullBatching

Когда в батче все пары тематик уникальные, то для каждого сэмпла в батче все сэмплы, расположенные не в этой строке по индексу, тоже являются нерелевантными. Эту информацию тоже нужно использовать. Это значит, что у нас не 32 примеров батча, а n2 от 32, то есть на самом деле 322, хотя в памяти хранится только изначальное число.

Этот FullBatching мы используем при вычислениях внутри Loss, что позволяет учесть гораздо больше информации. Также это позволяет умещаться в памяти, не используя при этом гораздо больший объем данных, увеличить скорость сходимости и точность. Мы видим за раз больше негативных и позитивных примеров, не увеличивая количество видимых сэмплов. Смотрим не только на свою пару, а на все.

Ускоряем обучение: p-tuning и адаптеры

«Вишенка на торте» — подход, который позволяет нам очень быстро переобучать наши модели при поставке нового контента. Все предыдущие этапы занимают от двух недель до месяца на большом суперкомпьютере вроде Christofari. Но когда у нас появляются новые диалоги, то модель на них тоже надо дообучить. При этом мы не можем под каждую новую поставку ставить модель в очередь на месяц-два.

Решение есть: использовать самый популярный в последнее время P-Learning или адаптеры. То есть фризим основную часть модели, а feed-forward слои — переобучаем, т.е. только определённые маленькие модельки поверх трансформера, тем самым просто смещая распределение каких-то примеров или лейблов.

Это позволяет очень быстро за один спринт, релизный цикл, получить модель с обновленными данными по контенту.

Inference

Расскажу, как мы ускоряли и облегчали наши модели.

Ускоряем и облегчаем inference

Когда мы говорим про скорость, у нас есть верхняя граница по latency. Если получается выиграть немного дополнительного времени, мы всегда задумываемся, как можно использовать больше фичей или модель побольше, потому что это напрямую влияет на онлайн метрики.

А ещё, когда мы говорим про скорость, подразумеваем скорость процессов — то есть скорость того, как быстро можно доставить изменения на продакшн, будь то багфиксы или новые фичи.

Принципы при внедрении нового ML-функционала

Важно, что все эти улучшения мы делаем при условии отсутствия деградации по определённым параметрам или принципам, которые мы для себя разработали:

метрики, за которыми мы следим;
удобство поддержания этого механизма;
возможность откатиться к прошлым версиям моделей;
быстрые итерации нововведений;
масштабируемость.

Общая схема работы

Разберём, как работают виртуальные ассистенты или conversation агенты.

Представьте, что у вас есть некая фраза от пользователя.

Всегда есть верхнеуровневый модуль Intent Recognizer, который роутирует трафик и определяет намерение пользователя: поставить таймер, включить музыку или пообщаться.

Дальше мы попадаем в модуль, про который и идёт речь в этой статье, — это общение на свободные темы. Здесь тоже есть внутренний intent recognizer, потому что трафик напрямую в «болталку» или чат-модель вы отправлять не будете. У вас есть некий набор интентов, которые, например, определяют характер персонажа. Это называется библия персонажа — как его зовут, как он выглядит, какие у него ответы. Или это могут быть какие-то кастомные сценарии или промо-акции, приуроченные к определённым датам. Поэтому и существует такое разделение.

Блок Annotators — это набор классификаторов поверх векторов, контекста, предложения или просто токенов, которые обогащают запрос. Эти предсказания можно использовать либо для сценарной логики, либо просто как фичи в ранжировщике, который подбирает наиболее интересную и релевантную реплику в диалоге.

Векторизация и модели-адаптеры

У нас есть двухэтапный подход:

Есть базовая, сильная модель-векторизатор, которая умеет матчить похожие по смыслу, но разные по написанию фразы в одну точку в семантическом пространстве. Потом мы используем целую плеяду разных очень простых и лёгких моделей, которые могут решить конкретную задачу. Например, определить, является ли текущий контекст провокационным, или идентифицировать эмоцию/тематику конкретного запроса. Это намного быстрее, чем обучать 20 огромных моделей, потому что модели маленькие.

Такой подход позволяет легко добавлять новый аннотатор или задачи. Нужно просто дообучить эту простую сетку на небольшом объёме данных. Здесь же можно говорить и про замену моделей, то есть они разделены. Но появляется момент, за которым нужно следить, — это консистентность. Когда следующая модель напрямую зависит от векторов предыдущей, важно следить за тем, что их версии совпадают. Ведь если при этом вектора не сильно разъедутся на простых функциональных тестах, этого можно даже не заметить.

Когда есть такое выделение базового векторизатора, его можно обложить и холодным, и горячим кэшем. Скажу по секрету: если вы возьмёте кэш в 40 тысяч разных фраз, то покроете половину распределения даже в «болталке». Ведь когда мы в жизни общаемся, используем примерно эти же фразы: «привет», «как дела» и так далее. Поэтому для этого можно использовать кэши и не гонять лишний раз большую тяжёлую модель.

Обсудим блоки распознавания интентов и ChitChat модель.

Задачи «Болталки» и ведения простой беседы можно решать двумя способами:

Использовать генеративные сети, которые авторегрессионно, токен за токеном восстанавливают ответ, к примеру, GPT. Мы так и делаем — используем большую сеть.
Решать задачу информационного поиска. Это когда есть огромная база из заготовленных реплик, нужно сметчить и достать наиболее подходящие под данный контекст реплики из этой базы, а потом их отранжировать.

Когда мы говорим про подход, основанный на поиске и распознавании интентов, задача сводится к векторизации текущего контекста. Это нужно, чтобы посмотреть, какие кандидаты лучше всего подходят и решается с помощью быстрого поиска ближайших соседей.

FAISS для быстрого поиска

Мы с самого начала начали использовать библиотеку для хранения и поиска информации в векторном представлении FAISS. Нашим требованием он в целом удовлетворял, поэтому и дальше использовали его.

Кусок на изображении выше — из ReadMe. То есть можно использовать буквально три строки.

Но есть нюанс. Дело в том, что быстрый поиск ближайших соседей мы используем для разных задач. Получается, что есть разные индексы, которые можно по-разному конфигурировать. Так как в нашем случае у нас нет большой базы в миллиард условно разных сэмплов, мы не используем Product Quantization, чтобы сжимать данные. Нам хватает перевести всё во float16.

Мы видим определённый трейд-офф между точностью, воспроизводимостью и скоростью, которая нас будет устраивать. Поэтому в случае распознавания интентов и «болталки», основанном на информационном поиске на этапе генерации кандидатов, мы используем связку нашего SBERT и FAISS. Здесь же, естественно, у нас заготовлены все кэши для базы, мы подобрали настройки.

Упомяну момент, которого в ReadMe нет — то, как вы будете загружать в память этот самый индекс. Можно либо на CPU, либо на GPU, при этом часть индексов будет на GPU. Можно сохранить весь большой индекс полностью, засериализовать и загружать. А можно создать индекс и загружать шардами. Второй вариант позволит избежать пики по памяти во время старта пода. Это может быть достаточно критично, потому что если вывалиться из памяти GPU, можно просто завязнуть в этом бесконечном рестарте.

Консистентность

Консистентность больше относится в целом ко всему проекту, а не только к двухэтапной системе аннотаторов.

Дело в том, что с самого начала прототипы делали просто: есть Docker-контейнер для проекта и модели, в котором мы хранили код. Естественно, это не тот путь, которому нужно следовать. Со временем мы разделили код и определённые конфигурации. Мы называем их «статики» — это наши модели и кэши.

Это нужно, потому что в большинстве компаний релизные процессы кода, статиков и весов модели отличаются по скорости. Поэтому в нашем случае намного удобнее в Docker держать исключительно код и библиотеки, которые исполняются. Тогда и Docker будет легче, а значит будет быстрее загружатся в registry и стартовать. А сами модели и кэши храним отдельно, и во время старта пода подтягиваем из бакета. Это даёт удобство: можно раздельно обновлять модели и быть уверенными, что всё в целом будет хорошо.

Но здесь нужны проверки:

Проверка совпадения версии между кодом и статиками.
Совпадение векторизатора и кэшей, которые к нему относятся.

Поэтому у нас есть множество разных проверок, которые оценивают консистентность между векторами кэшей и векторизатора.

Выводы

На изображении выше указаны пункты, которые принесли нам больше всего пользы с точки зрения обучения и inference:

Мультитаск, когда модель базово обучается на разные синергичные задачи — те, которые не сильно разделяют эмбеддинги между собой. Так можно получить более сильную модель. Мульти-GPU на HOROVOD, а батч — побольше. Так мы получаем более сильную базовую модель векторизатора.
Поиск на inference. Есть поисковый запрос и база, которая помогает уменьшить размерность. То есть когда у нас в базе лежит не 1000 float32 на каждое предложение, а всего 300, это здорово экономит память.
Adversarial атаки. Только начав, мы просто хотели повысить консистентность к опечаткам и к ошибкам ASR. Но эта штука оказалась действительно классной. Это очень дешёвое действие, которое позволяет и улучшить сходимость, и подтянуть метрики, и сделать модель более устойчивой.
Дистилляция.
Для inference, рекомендуем:

- Использовать кэши, где это возможно, в рамках разумного.

- Использовать библиотеку для быстрого поиска ближайших соседей.

- Наладить CI/CD процессы.

- Подумать про двухэтапный подход, когда нужно проаннотировать или проставить метки для текущего контекста. То есть сделать одну базовую модель-векторизатор и множество маленьких, которые решают каждая свою задачу. Причём их можно тренировать прямо на этапе мультитаска, а потом отдельно тюнить.

- Переводить модели в специальные форматы. Мы все модели переводим в специальные форматы для inference, благо, они есть как у TensorFlow, так и у PyTorch. Это позволяет не делать ненужных вычислений во время inference и ужимать сами модели.

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13 авг. 2024 г.

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
26.06.24 18:46 Jacobethannn098

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04.07.24 04:49 ZionNaomi

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13.07.24 21:13 michaelharrell825

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17.07.24 02:26 thompsonrickey

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18.07.24 20:13 austinagastya

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27.08.24 12:50 James889900

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27.08.24 13:06 James889900

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02.09.24 20:24 [email protected]

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06.09.24 01:35 Celinagarcia

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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.
16.09.24 00:10 marcusaustin

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16.09.24 00:11 marcusaustin

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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.
01.10.24 14:54 Sinewclaudia

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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.
18.10.24 09:34 freidatollerud

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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.
02.11.24 14:44 diannamendoza732

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12.11.24 00:50 TERESA

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17.11.24 09:31 Vivianlocke223

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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
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
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!
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.
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
22.11.24 15:26 cliftonhandyman

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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 >
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
25.11.24 02:19 briankennedy

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25.11.24 02:20 briankennedy

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