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, 07:15 UTC
[doc] small fix (#19167)
Signed-off-by: reidliu41 <reid201711@gmail.com> Co-authored-by: reidliu41 <reid201711@gmail.com>
Reid committed
Jun 5, 2025 at 09:13 UTC
78dcf56cb31f8abb7d9ae3ba02ce9822eba34820
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docs/models/extensions/tensorizer.md
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@@ -10,7 +10,7 @@ shorter Pod startup times and CPU memory usage. Tensor encryption is also suppor
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For more information on CoreWeave's Tensorizer, please refer to
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[CoreWeave's Tensorizer documentation](https://github.com/coreweave/tensorizer). For more information on serializing a vLLM model, as well a general usage guide to using Tensorizer with vLLM, see
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-the [vLLM example script](https://docs.vllm.ai/en/latest/examples/tensorize_vllm_model.html).
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+the [vLLM example script](https://docs.vllm.ai/en/latest/examples/others/tensorize_vllm_model.html).
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!!! note
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Note that to use this feature you will need to install `tensorizer` by running `pip install vllm[tensorizer]`.