A high-throughput and memory-efficient inference and serving engine for LLMs
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[Doc]: update paths for Offline/Online/Others example sections (#33494)
Signed-off-by: Sawyer Bowerman <sbowerma@redhat.com> Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Sawyer Bowerman committed
Feb 1, 2026 at 22:56 UTC
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docs/examples/README.md
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vLLM's examples are split into three categories:
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-- If you are using vLLM from within Python code, see the *Offline Inference* section.
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-- If you are using vLLM from an HTTP application or client, see the *Online Serving* section.
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-- For examples of using some of vLLM's advanced features (e.g. LMCache or Tensorizer) which are not specific to either of the above use cases, see the *Others* section.
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+- If you are using vLLM from within Python code, see the [Offline Inference](../../examples/offline_inference) section.
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+- If you are using vLLM from an HTTP application or client, see the [Online Serving](../../examples/online_serving) section.
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+- For examples of using some of vLLM's advanced features (e.g. LMCache or Tensorizer) which are not specific to either of the above use cases, see the [Others](../../examples/others) section.