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Signed-off-by: wang.yuqi <yuqi.wang@daocloud.io> Signed-off-by: wang.yuqi <noooop@126.com> Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com> Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com> Co-authored-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
Summary
!!! important
Many decoder language models can now be automatically loaded using the Transformers modeling backend without having to implement them in vLLM. See if vllm serve <model> works first!
vLLM models are specialized PyTorch models that take advantage of various features to optimize their performance.
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).
Read through these pages for a step-by-step guide:
!!! tip If you are encountering issues while integrating your model into vLLM, feel free to open a GitHub issue or ask on our developer slack. We will be happy to help you out!