Signed-off-by: zxw <1020938856@qq.com>
This commit is contained in:
@@ -34,7 +34,7 @@ llm.apply_model(lambda model: print(type(model)))
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If it is `TransformersForCausalLM` then it means it's based on Transformers!
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!!! tip
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You can force the use of `TransformersForCausalLM` by setting `model_impl="transformers"` for [offline-inference][offline-inference] or `--model-impl transformers` for the [openai-compatible-server][openai-compatible-server].
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You can force the use of `TransformersForCausalLM` by setting `model_impl="transformers"` for [offline-inference][offline-inference] or `--model-impl transformers` for the [openai-compatible-server][serving-openai-compatible-server].
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!!! note
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vLLM may not fully optimise the Transformers implementation so you may see degraded performance if comparing a native model to a Transformers model in vLLM.
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@@ -53,8 +53,8 @@ For a model to be compatible with the Transformers backend for vLLM it must:
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If the compatible model is:
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- on the Hugging Face Model Hub, simply set `trust_remote_code=True` for [offline-inference][offline-inference] or `--trust-remote-code` for the [openai-compatible-server][openai-compatible-server].
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- in a local directory, simply pass directory path to `model=<MODEL_DIR>` for [offline-inference][offline-inference] or `vllm serve <MODEL_DIR>` for the [openai-compatible-server][openai-compatible-server].
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- on the Hugging Face Model Hub, simply set `trust_remote_code=True` for [offline-inference][offline-inference] or `--trust-remote-code` for the [openai-compatible-server][serving-openai-compatible-server].
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- in a local directory, simply pass directory path to `model=<MODEL_DIR>` for [offline-inference][offline-inference] or `vllm serve <MODEL_DIR>` for the [openai-compatible-server][serving-openai-compatible-server].
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This means that, with the Transformers backend for vLLM, new models can be used before they are officially supported in Transformers or vLLM!
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