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Самая мощная LLM в опесорсе, Mixtral 8x7B MoE от Mistral AI, теперь доступна во фреймворке Сandle* - с поддержкой квантизации. За счет квантизации модели могут работать локально на ноутбуке с 32 GB RAM.

Например, 4-битная Mixtral 8x7B MoE занимает всего 26.44GB памяти. Тогда как в bf16 на GPU модель бы заняла 112+ GB VRAM (то есть влезла бы только на H100).

*Candle - это минималистский ML-фреймворк для Rust, сфокусированный на производительности (включая поддержку GPU) и простоте использования.

- Поддерживает 2-bit, 3-bit, 4-bit, 5-bit, 6-bit and 8-bit int квантизованные модели в gguf and ggml форматах.
- SIMD оптимизации для Apple Silicon и x86.

Вот тут можете попробовать демки разных моделей на Candle:
- Whisper, [пост в канале]
- LLaMa-2, [пост в канале]
- T5,
- YOLOv8,
- Segment Anything [пост в канале]

@ai_newz



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Самая мощная LLM в опесорсе, Mixtral 8x7B MoE от Mistral AI, теперь доступна во фреймворке Сandle* - с поддержкой квантизации. За счет квантизации модели могут работать локально на ноутбуке с 32 GB RAM.

Например, 4-битная Mixtral 8x7B MoE занимает всего 26.44GB памяти. Тогда как в bf16 на GPU модель бы заняла 112+ GB VRAM (то есть влезла бы только на H100).

*Candle - это минималистский ML-фреймворк для Rust, сфокусированный на производительности (включая поддержку GPU) и простоте использования.

- Поддерживает 2-bit, 3-bit, 4-bit, 5-bit, 6-bit and 8-bit int квантизованные модели в gguf and ggml форматах.
- SIMD оптимизации для Apple Silicon и x86.

Вот тут можете попробовать демки разных моделей на Candle:
- Whisper, [пост в канале]
- LLaMa-2, [пост в канале]
- T5,
- YOLOv8,
- Segment Anything [пост в канале]

@ai_newz

BY эйай ньюз


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