A high-throughput and memory-efficient inference and serving engine for LLMs
Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git
Synced Nov 15, 16:00 UTC
[Docs] Fix small error in link text (#15868)
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
Harry Mellor committed
Apr 1, 2025 at 11:05 UTC
d330558bab70ce760ea70433f3e9846a909640a1
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docs/source/models/supported_models.md
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@@ -135,7 +135,7 @@ To determine whether a given model is natively supported, you can check the `con
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If the `"architectures"` field contains a model architecture listed below, then it should be natively supported.
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Models do not _need_ to be natively supported to be used in vLLM.
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-The <project:#transformers-backend> enables you to run models directly using their Transformers implementation (or even remote code on the Hugging Face Model Hub!).
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+The [Transformers backend](#transformers-backend) enables you to run models directly using their Transformers implementation (or even remote code on the Hugging Face Model Hub!).
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:::{tip}
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The easiest way to check if your model is really supported at runtime is to run the program below: