danieldk opened a new issue, #595:
URL: https://github.com/apache/tvm-ffi/issues/595

   Hi 👋. I am one of the core team members of the Hugging Face Kernels project: 
https://huggingface.co/docs/kernels/ The goal of the kernels project is to make 
it easy for kernel developers to write and distribute kernels and for kernel 
users to use kernels in their favorite models. The project consists of several 
parts:
   
   * `kernel-builder`: builds kernels for multiple systems (OS + arch), 
backends (CUDA, XPU, ROCm, Metal and multiple versions of each), and framework 
versions (e.g. multiple Torch versions).
   * Kernel Hub: which can be used for distribution of kernels. There are quite 
some kernels already available from us and from third-parties: 
https://huggingface.co/kernels
   * The `kernels` Python client. Using the Python client, users can download 
and load kernels using simply:
      
      ```
      import kernels
      fa3 = kernels.get_kernel("kernels-community/flash-attn3", version=1)
      ```
   
      `kernels` will take care of download and loading the right variant for a 
user's system.
   
   So far, we have focused primarily on Torch support, but I think TVM FFI fits 
in well with our goal of making it easy to build and load kernels, especially 
because it would make Hub kernels available for frameworks beyond Torch. A 
while ago, we implemented initial support for building and loading TVM FFI 
kernels. There is a minimal example at: 
https://github.com/huggingface/kernels/tree/main/examples/kernels/relu-tvm-ffi 
, with the built kernel at: 
https://huggingface.co/kernels/kernels-test/relu-tvm-ffi
   
   We would love to collaborate more if you are interested - we have a bunch of 
questions around encoding ABI versions, etc. If you are interested, we could 
set up a shared Slack channel or otherwise communicate through this issue.


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