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🧠 FlexAttention — простой способ писать любое внимание на PyTorch

Зачем городить сложные CUDA-ядра, если можно использовать понятный и мощный абстрактный подход?

FlexAttention — это новая модель программирования, которая позволяет реализовать большинство вариантов attention (внимания) всего в *нескольких строках кода на PyTorch*.

⚙️ Работает на базе компилятора — автоматически оптимизирует вычисления
🚀 Производительность на уровне кастомных ядер (hand-written kernels)

📌 Что даёт FlexAttention:
• Унифицированный способ писать self-, cross-, local-, sparse-attention
• Без кастомных CUDA/CPP — всё на чистом PyTorch
• Гибкость и читаемость для исследований и прототипов

🎥 Смотреть

Анализ данных (Data analysis)
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🧠 FlexAttention — простой способ писать любое внимание на PyTorch

Зачем городить сложные CUDA-ядра, если можно использовать понятный и мощный абстрактный подход?

FlexAttention — это новая модель программирования, которая позволяет реализовать большинство вариантов attention (внимания) всего в *нескольких строках кода на PyTorch*.

⚙️ Работает на базе компилятора — автоматически оптимизирует вычисления
🚀 Производительность на уровне кастомных ядер (hand-written kernels)

📌 Что даёт FlexAttention:
• Унифицированный способ писать self-, cross-, local-, sparse-attention
• Без кастомных CUDA/CPP — всё на чистом PyTorch
• Гибкость и читаемость для исследований и прототипов

🎥 Смотреть
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Анализ данных (Data analysis)



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🧠 FlexAttention — простой способ писать любое внимание на PyTorch

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