Post
3407
stop writing CUDA kernels yourself
we have launched Kernel Hub: easy optimized kernels for all models on Hugging Face 🔥 use them right away!
it's where the community populates optimized kernels 🤝
this release comes in three parts
> Kernel Hub: contains (as of now) 14 kernels
> kernels: Python library to load kernels from Kernel Hub
> kernel-builder: Nix package to build kernels for PyTorch (made using PyTorch C++ frontend)
when building models, your regular workflow should be pulling kernels from Hub and building your model with them 🤗
here's a practical example with RMSNorm:
1. pull the kernel from Hub with
2. decorate with
3. inject it to your model
we'd love to hear your feedback! 🙏🏻
we also welcome kernel contributions by community 🥹💗
- request kernels here: kernels-community/README#1
- check out this org:
kernels-community
- read the blog: https://huggingface.co/blog/hello-hf-kernels
we have launched Kernel Hub: easy optimized kernels for all models on Hugging Face 🔥 use them right away!
it's where the community populates optimized kernels 🤝
this release comes in three parts
> Kernel Hub: contains (as of now) 14 kernels
> kernels: Python library to load kernels from Kernel Hub
> kernel-builder: Nix package to build kernels for PyTorch (made using PyTorch C++ frontend)
when building models, your regular workflow should be pulling kernels from Hub and building your model with them 🤗
here's a practical example with RMSNorm:
1. pull the kernel from Hub with
get_kernel2. decorate with
use_kernel_forward_from_hub3. inject it to your model
we'd love to hear your feedback! 🙏🏻
we also welcome kernel contributions by community 🥹💗
- request kernels here: kernels-community/README#1
- check out this org:
kernels-community
- read the blog: https://huggingface.co/blog/hello-hf-kernels
