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MSLK Library

MSLK (Meta Superintelligence Labs Kernels, formerly known as FBGEMM GenAI) is a collection of high-performance kernels and optimizations built on top of PyTorch primitives for GenAI training and inference.

Installation

# Full MSLK library
pip install mslk-cuda==1.0.0
pip install mslk==1.0.0 --index-url https://download.pytorch.org/whl/cu128

Releases Compatibility Table

MSLK is released in accordance to the PyTorch release schedule, and each release has no guarantee to work in conjunction with PyTorch releases that are older than the one that the MSLK release corresponds to.

MSLK Release Corresponding PyTorch Release Supported Python Versions Supported CUDA Versions Supported CUDA Architectures Supported ROCm Versions Supported ROCm Architectures
1.0.0 2.10.x 3.10, 3.11, 3.12 3.13, 3.14 12.6, 12.8, 12.9, 13.0 8.0, 9.0a, 10.0a, 12.0a 7.0, 7.1 gfx908, gfx90a, gfx942, gfx950

Join the MSLK community

For questions, support, news updates, or feature requests, please feel free to:

For contributions, please see the CONTRIBUTING file for ways to help out.

License

MSLK is BSD licensed, as found in the LICENSE file.

About

MSLK (Meta Superintelligence Labs Kernels) is a collection of PyTorch GPU operator libraries that are designed and optimized for GenAI training and inference, such as FP8 row-wise quantization and collective communications.

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  • Python 39.7%
  • Cuda 22.6%
  • C++ 17.8%
  • HIP 14.5%
  • C 2.3%
  • Shell 2.3%
  • CMake 0.8%