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«Large Lambda Model» крутой гайд, где автор делится опытом реализации инференса модели GPT-2 на языке Haskell с использованием библиотеки hmatrix и OpenBLAS.

Основная цель проекта — выполнить прямой проход (forward pass) модели без обучения или обратного распространения ошибки.

Этот проект демонстрирует, как можно реализовать инференс модели GPT-2 на Haskell, углубляясь в детали архитектуры и работы с линейной алгеброй без использования специализированных тензорных библиотек.

Выбор инструментов:
Haskell и hmatrix: Использование Haskell с hmatrix для линейной алгебры.
OpenBLAS: Применение для оптимизации линейных операций.
Архитектура GPT-2:


Ресурсы для изучения:
- Репозитории Karpathy: NanoGPT и llm.c.
Визуализатор LLM от Brendan Bycroft.
Веб-приложение для токенизации: tiktokenizer.

▪ Читать

@haskell_tg

Haskell
«Large Lambda Model» крутой гайд, где автор делится опытом реализации инференса модели GPT-2 на языке Haskell с использованием библиотеки hmatrix и OpenBLAS.

Основная цель проекта — выполнить прямой проход (forward pass) модели без обучения или обратного распространения ошибки.

Этот проект демонстрирует, как можно реализовать инференс модели GPT-2 на Haskell, углубляясь в детали архитектуры и работы с линейной алгеброй без использования специализированных тензорных библиотек.

Выбор инструментов:
Haskell и hmatrix: Использование Haskell с hmatrix для линейной алгебры.
OpenBLAS: Применение для оптимизации линейных операций.
Архитектура GPT-2:


Ресурсы для изучения:
- Репозитории Karpathy: NanoGPT и llm.c.
Визуализатор LLM от Brendan Bycroft.
Веб-приложение для токенизации: tiktokenizer.

▪ Читать

@haskell_tg
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«Large Lambda Model» крутой гайд

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