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Jun 26, 2025
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[Doc] Update docs for New Model Implementation #20115

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732ffb9
[DOc] Clean up new model docs
DarkLight1337 Jun 26, 2025
af11768
Fix nav
DarkLight1337 Jun 26, 2025
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5 changes: 4 additions & 1 deletion docs/.nav.yml
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Expand Up @@ -48,7 +48,10 @@ nav:
- General:
- glob: contributing/*
flatten_single_child_sections: true
- Model Implementation: contributing/model
- Model Implementation:
- contributing/model/README.md
- contributing/model/*
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medium

The glob pattern * will expand to all files in the contributing/model/ directory, including README.md and multimodal.md which are already listed explicitly. This is likely to cause duplicate entries in the navigation menu.

To avoid this and to control the order of pages, it's better to explicitly list the files you want to include between README.md and multimodal.md.

      - contributing/model/basic.md
      - contributing/model/registration.md
      - contributing/model/tests.md

- contributing/model/multimodal.md
- Design Documents:
- V0: design
- V1: design/v1
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24 changes: 13 additions & 11 deletions docs/contributing/model/README.md
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@@ -1,21 +1,23 @@
---
title: Adding a New Model
title: Summary
---
[](){ #new-model }

This section provides more information on how to integrate a [PyTorch](https://pytorch.org/) model into vLLM.
!!! important
Many decoder language models can now be automatically loaded using the [Transformers backend][transformers-backend] without having to implement them in vLLM. See if `vllm serve <model>` works first!

Contents:
vLLM models are specialized [PyTorch](https://pytorch.org/) models that take advantage of various [features][compatibility-matrix] to optimize their performance.

- [Basic](basic.md)
- [Registration](registration.md)
- [Tests](tests.md)
- [Multimodal](multimodal.md)
The complexity of integrating a model into vLLM depends heavily on the model's architecture.
The process is considerably straightforward if the model shares a similar architecture with an existing model in vLLM.
However, this can be more complex for models that include new operators (e.g., a new attention mechanism).

!!! note
The complexity of adding a new model depends heavily on the model's architecture.
The process is considerably straightforward if the model shares a similar architecture with an existing model in vLLM.
However, for models that include new operators (e.g., a new attention mechanism), the process can be a bit more complex.
Read through these pages for a step-by-step guide:

- [Implementing a Basic Model](basic.md)
- [Registering a Model to vLLM](registration.md)
- [Writing Unit Tests](tests.md)
- [Multi-Modal Support](multimodal.md)

!!! tip
If you are encountering issues while integrating your model into vLLM, feel free to open a [GitHub issue](https://github.com/vllm-project/vllm/issues)
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