Describe the get_kernel/LayerRepository

This was already in the API documentation, but describe this in the
guides as well (since we want people to use versions).

docs/source/basic-usage.md

@@ -21,6 +21,22 @@ activation.gelu_fast(y, x)
 print(y)
 ```
 
+### Using version bounds
+
+Kernels are versioned using tags of the form `v<major>.<minor>.<patch>`.
+You can specify which version to download using Python version specifiers:
+
+```python
+import torch
+from kernels import get_kernel
+
+activation = get_kernel("kernels-community/activation", version=">=0.0.4,<0.1.0")
+```
+
+This will get the latest kernel tagged `v0.0.z` where `z` is at least 4. It
+is strongly recommended to specify a version bound, since a kernel author
+might push incompatible changes to the `main` branch.
+
 ## Checking Kernel Availability
 
 You can check if a specific kernel is available for your environment:

docs/source/kernel-requirements.md

@@ -34,6 +34,8 @@ Kernels are versioned on the Hub using Git tags. Version tags must be of
 the form `v<major>.<minor>.<patch>`. Versions are used by [locking](./locking.md)
 to resolve the version constraints.
 
+We recommend using [semver](https://semver.org/) to version kernels.
+
 ## Native Python module
 
 Kernels will typically contain a native Python module with precompiled
@@ -50,7 +52,6 @@ have dynamic library dependencies outside:
   for compatibility with Python 3.9 and later.
 - Compatible with [`manylinux_2_28`](https://github.com/pypa/manylinux?tab=readme-ov-file#manylinux_2_28-almalinux-8-based).
   This means that the extension **must not** use symbols versions higher than:
-
   - GLIBC 2.28
   - GLIBCXX 3.4.24
   - CXXABI 1.3.11

docs/source/layers.md

@@ -157,6 +157,33 @@ with use_kernel_mapping(kernel_layer_mapping):
 This ensures that the mapping is not active anymore outside the
 `with`-scope.
 
+### Using version bounds
+
+Kernels are versioned using tags of the form `v<major>.<minor>.<patch>`.
+You can specify which version of the kernel to download using Python version
+specifiers:
+
+```python
+kernel_layer_mapping = {
+    "SiluAndMul": {
+        "cuda": LayerRepository(
+            repo_id="kernels-community/activation",
+            layer_name="SiluAndMul",
+            version=">=0.0.4,<0.1.0",
+        ),
+        "rocm": LayerRepository(
+            repo_id="kernels-community/activation",
+            layer_name="SiluAndMul",
+            version=">=0.0.4,<0.1.0",
+        )
+    }
+}
+```
+
+This will get the layer from latest kernel tagged `v0.0.z` where `z` is at
+least 4. It is strongly recommended to specify a version bound, since a
+kernel author might push incompatible changes to the `main` branch.
+
 ### Registering kernels for specific modes
 
 You might want to register two different kernels for a particular layer,