A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
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[Docs] fix invalid doc link (#25017)
Signed-off-by: zxw <1020938856@qq.com>
yyzxw committed
Sep 17, 2025 at 11:53 UTC
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docs/contributing/model/README.md
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!!! important
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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!
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-vLLM models are specialized [PyTorch](https://pytorch.org/) models that take advantage of various [features](../../features/compatibility_matrix.md) to optimize their performance.
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+vLLM models are specialized [PyTorch](https://pytorch.org/) models that take advantage of various [features](../../features/README.md#compatibility-matrix) to optimize their performance.
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The complexity of integrating a model into vLLM depends heavily on the model's architecture.
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The process is considerably straightforward if the model shares a similar architecture with an existing model in vLLM.