k-bit optimizers and matrix multiplication routines.

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  • License: MIT License (MIT License)
  • Author: Tim Dettmers
  • Maintainer: Titus von Köller
  • Tags gpu, optimizers, optimization, 8-bit, quantization, compression
  • Requires: Python >=3.8
  • Provides-Extra: benchmark, docs, dev, test
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bitsandbytes

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The bitsandbytes library is a lightweight Python wrapper around CUDA custom functions, in particular 8-bit optimizers, matrix multiplication (LLM.int8()), and 8 & 4-bit quantization functions.

The library includes quantization primitives for 8-bit & 4-bit operations, through bitsandbytes.nn.Linear8bitLt and bitsandbytes.nn.Linear4bit and 8-bit optimizers through bitsandbytes.optim module.

There are ongoing efforts to support further hardware backends, i.e. Intel CPU + GPU, AMD GPU, Apple Silicon, hopefully NPU.

Please head to the official documentation page:

https://huggingface.co/docs/bitsandbytes/main

License

bitsandbytes is MIT licensed.

We thank Fabio Cannizzo for his work on FastBinarySearch which we use for CPU quantization.

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Avatar for timdettmers from gravatar.com timdettmers Avatar for Titus-von-Koeller from gravatar.com Titus-von-Koeller

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  • License: MIT License (MIT License)
  • Author: Tim Dettmers
  • Maintainer: Titus von Köller
  • Tags gpu, optimizers, optimization, 8-bit, quantization, compression
  • Requires: Python >=3.8
  • Provides-Extra: benchmark, docs, dev, test
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