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karylab_agents/vllm
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khluu/vllm-base-uv-python
vllm/docs/configuration
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pschlan-amdGitHubTJian
0098db9ec1 [ROCm] Implement GPU-to-NUMA-node detection (#40015)
Signed-off-by: Patrick Schlangen <pschlan@amd.com>
Co-authored-by: TJian <tunjian.tan@embeddedllm.com>
2026-04-23 10:08:48 -05:00
..
conserving_memory.md
[Hardware] Replace torch.cuda.device_count/current_device/set_device API (#36145)
2026-03-12 07:57:47 -07:00
engine_args.md
[Docs] Fix some snippets (#31378)
2025-12-26 12:47:41 +00:00
env_vars.md
[Docs] Take env var definition out of folded admonition (#29005)
2025-11-19 03:32:04 -08:00
model_resolution.md
[Misc] unify variable for LLM instance (#20996)
2025-07-21 12:18:33 +01:00
optimization.md
[ROCm] Implement GPU-to-NUMA-node detection (#40015)
2026-04-23 10:08:48 -05:00
README.md
[Docs] Replace all explicit anchors with real links (#27087)
2025-10-17 02:22:06 -07:00
serve_args.md
[Doc] Fix failing doc build (#28772)
2025-11-15 05:33:27 -08:00

README.md

Configuration Options

This section lists the most common options for running vLLM.

There are three main levels of configuration, from highest priority to lowest priority:

  • Request parameters and input arguments
  • Engine arguments
  • Environment variables
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