https://github.com/TimDettmers/bitsandbytes

Accessible large language models via k-bit quantization for PyTorch.
https://github.com/TimDettmers/bitsandbytes

llm machine-learning pytorch qlora quantization

Last synced: 26 days ago
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Accessible large language models via k-bit quantization for PyTorch.

• Host: GitHub
• URL: https://github.com/TimDettmers/bitsandbytes
• Owner: bitsandbytes-foundation
• License: mit
• Created: 2021-06-04T00:10:34.000Z (almost 4 years ago)
• Default Branch: main
• Last Pushed: 2025-03-14T21:21:11.000Z (about 1 month ago)
• Last Synced: 2025-03-16T23:48:49.176Z (about 1 month ago)
• Topics: llm, machine-learning, pytorch, qlora, quantization
• Language: Python
• Homepage: https://huggingface.co/docs/bitsandbytes/main/en/index
• Size: 2.73 MB
• Stars: 6,806
• Watchers: 51
• Forks: 675
• Open Issues: 196
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

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README

        
# `bitsandbytes`

[![Downloads](https://static.pepy.tech/badge/bitsandbytes)](https://pepy.tech/project/bitsandbytes) [![Downloads](https://static.pepy.tech/badge/bitsandbytes/month)](https://pepy.tech/project/bitsandbytes) [![Downloads](https://static.pepy.tech/badge/bitsandbytes/week)](https://pepy.tech/project/bitsandbytes)

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](https://huggingface.co/docs/bitsandbytes/main)**

## License

`bitsandbytes` is MIT licensed.

We thank Fabio Cannizzo for his work on [FastBinarySearch](https://github.com/fabiocannizzo/FastBinarySearch) which we use for CPU quantization.