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[Doc][3/N] Reorganize Serving section (#11766)

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Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
This commit is contained in:
Cyrus Leung
2025-01-07 11:20:01 +08:00
committed by GitHub
parent d93d2d74fd
commit 8ceffbf315
40 changed files with 248 additions and 133 deletions
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docs/source/contributing/dockerfile/dockerfile.md
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@@ -1,7 +1,7 @@
# Dockerfile
We provide a <gh-file:Dockerfile> to construct the image for running an OpenAI compatible server with vLLM.
More information about deploying with Docker can be found [here](../../serving/deploying_with_docker.md).
More information about deploying with Docker can be found [here](#deployment-docker).
Below is a visual representation of the multi-stage Dockerfile. The build graph contains the following nodes:

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docs/source/contributing/model/registration.md
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# Model Registration
vLLM relies on a model registry to determine how to run each model.
A list of pre-registered architectures can be found on the [Supported Models](#supported-models) page.
A list of pre-registered architectures can be found [here](#supported-models).
If your model is not on this list, you must register it to vLLM.
This page provides detailed instructions on how to do so.
@@ -16,7 +16,7 @@ This gives you the ability to modify the codebase and test your model.
After you have implemented your model (see [tutorial](#new-model-basic)), put it into the <gh-dir:vllm/model_executor/models> directory.
Then, add your model class to `_VLLM_MODELS` in <gh-file:vllm/model_executor/models/registry.py> so that it is automatically registered upon importing vLLM.
You should also include an example HuggingFace repository for this model in <gh-file:tests/models/registry.py> to run the unit tests.
Finally, update the [Supported Models](#supported-models) documentation page to promote your model!
Finally, update our [list of supported models](#supported-models) to promote your model!
```{important}
The list of models in each section should be maintained in alphabetical order.