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Add back README to the Python package #222
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| # kernels | ||
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| The Kernel Hub allows Python libraries and applications to load compute | ||
| kernels directly from the [Hub](https://hf.co/). To support this kind | ||
| of dynamic loading, Hub kernels differ from traditional Python kernel | ||
| packages in that they are made to be: | ||
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| - Portable: a kernel can be loaded from paths outside `PYTHONPATH`. | ||
| - Unique: multiple versions of the same kernel can be loaded in the | ||
| same Python process. | ||
| - Compatible: kernels must support all recent versions of Python and | ||
| the different PyTorch build configurations (various CUDA versions | ||
| and C++ ABIs). Furthermore, older C library versions must be supported. | ||
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| The `kernels` Python package is used to load kernels from the Hub. | ||
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| ## 🚀 Quick Start | ||
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| Install the `kernels` package with `pip` (requires `torch>=2.5` and CUDA): | ||
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| ```bash | ||
| pip install kernels | ||
| ``` | ||
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| Here is how you would use the [activation](https://huggingface.co/kernels-community/activation) kernels from the Hugging Face Hub: | ||
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| ```python | ||
| import torch | ||
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| from kernels import get_kernel | ||
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| # Download optimized kernels from the Hugging Face hub | ||
| activation = get_kernel("kernels-community/activation") | ||
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| # Random tensor | ||
| x = torch.randn((10, 10), dtype=torch.float16, device="cuda") | ||
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| # Run the kernel | ||
| y = torch.empty_like(x) | ||
| activation.gelu_fast(y, x) | ||
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| print(y) | ||
| ``` | ||
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| You can [search for kernels](https://huggingface.co/models?other=kernels) on | ||
| the Hub. | ||
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| ## 📚 Documentation | ||
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| Read the [documentation of kernels](https://huggingface.co/docs/kernels/). | ||
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I didn't put the logo image here, since it takes up a lot of valuable space on PyPI and we it's slow to load (as long as we don't have an SVG).