serving-llms-vllm

SKILLWorkflowcommunauté
v0.0.0Orchestra-ResearchMITMis à jour il y a 2 moisSource →

Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.

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il y a 2 moisDernière mise à jour
Skill
AuteurOrchestra-Research
Version0.0.0
LicenceMIT
CatégorieWorkflow
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À propos

Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.

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