Add back README to the Python package (#222)

Author: danieldk

README.md

@@ -23,9 +23,15 @@ packages in that they are made to be:
   the different PyTorch build configurations (various CUDA versions
   and C++ ABIs). Furthermore, older C library versions must be supported.
 
+## Components
+
+- You can load kernels from the Hub using the [`kernels`](kernels/) Python package.
+- If you are a kernel author, you can build your kernels with [kernel-builder](builder/).
+- Hugging Face maintains a set of kernels in [kernels-community](https://huggingface.co/kernels-community).
+
 ## 🚀 Quick Start
 
-Install the `kernels` package with `pip` (requires `torch>=2.5` and CUDA):
+Install the `kernels` Python package with `pip` (requires `torch>=2.5` and CUDA):
 
 ```bash
 pip install kernels

kernels/README.md

@@ -0,0 +1,50 @@
+# kernels
+
+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:
+
+- 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.
+
+The `kernels` Python package is used to load kernels from the Hub.
+
+## 🚀 Quick Start
+
+Install the `kernels` package with `pip` (requires `torch>=2.5` and CUDA):
+
+```bash
+pip install kernels
+```
+
+Here is how you would use the [activation](https://huggingface.co/kernels-community/activation) kernels from the Hugging Face Hub:
+
+```python
+import torch
+
+from kernels import get_kernel
+
+# Download optimized kernels from the Hugging Face hub
+activation = get_kernel("kernels-community/activation")
+
+# Random tensor
+x = torch.randn((10, 10), dtype=torch.float16, device="cuda")
+
+# Run the kernel
+y = torch.empty_like(x)
+activation.gelu_fast(y, x)
+
+print(y)
+```
+
+You can [search for kernels](https://huggingface.co/models?other=kernels) on
+the Hub.
+
+## 📚 Documentation
+
+Read the [documentation of kernels](https://huggingface.co/docs/kernels/).