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danieldk  updated a model about 5 hours ago
kernels-community/activation
drbh  updated a Space about 11 hours ago
kernels-community/README
danieldk  updated a model about 16 hours ago
kernels-community/relu
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Kernels Community

Kernels Community

The Kernel Hub allows Python libraries and applications to load optimized compute kernels directly from the Hugging Face Hub.

You can think of it as the Model Hub, but for low-level, high-performance code (kernels) that accelerate specific operations, often on GPUs.

Instead of manually managing complex dependencies, dealing with compilation flags, or building libraries like Triton or CUTLASS from source, the kernels library lets you fetch and run pre-compiled, optimized kernels on demand.


Repos

The Kernel Hub team maintains two core repos:

kernels

The main repository containing:

  • A deterministic kernel builder
  • A Python library for loading and executing kernels

Documentation:
https://huggingface.co/docs/kernels/

kernels-community

A repository that contains the source code for all of the kernels-community kernels

Source code:
https://github.com/huggingface/kernels-community


Compliant Kernels

Kernels published on the Hub are designed to be:

  • Portable — loadable from paths outside PYTHONPATH
  • Isolated — multiple kernel versions can run in the same process
  • Compatible — support different Python versions, PyTorch builds, and C++ ABIs

Learn more about the Kernel Hub and the kernels library by reading the docs:
https://huggingface.co/docs/kernels/index

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kernels-community (kernels-community)

AI & ML interests

None defined yet.

Recent Activity

danieldk  updated a model about 5 hours ago
kernels-community/activation
drbh  updated a Space about 11 hours ago
kernels-community/README
danieldk  updated a model about 16 hours ago
kernels-community/relu
View all activity

Kernels Community

Kernels Community

The Kernel Hub allows Python libraries and applications to load optimized compute kernels directly from the Hugging Face Hub.

You can think of it as the Model Hub, but for low-level, high-performance code (kernels) that accelerate specific operations, often on GPUs.

Instead of manually managing complex dependencies, dealing with compilation flags, or building libraries like Triton or CUTLASS from source, the kernels library lets you fetch and run pre-compiled, optimized kernels on demand.


Repos

The Kernel Hub team maintains two core repos:

kernels

The main repository containing:

  • A deterministic kernel builder
  • A Python library for loading and executing kernels

Documentation:
https://huggingface.co/docs/kernels/

kernels-community

A repository that contains the source code for all of the kernels-community kernels

Source code:
https://github.com/huggingface/kernels-community


Compliant Kernels

Kernels published on the Hub are designed to be:

  • Portable — loadable from paths outside PYTHONPATH
  • Isolated — multiple kernel versions can run in the same process
  • Compatible — support different Python versions, PyTorch builds, and C++ ABIs

Learn more about the Kernel Hub and the kernels library by reading the docs:
https://huggingface.co/docs/kernels/index

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