{
 "schema_version": 1,
 "generated": "2026-10-23",
 "id": "vllm-project-vllm--serve-lora-adapters-from-one-base-model",
 "repo": "vllm-project/vllm",
 "repo_url": "https://github.com/vllm-project/vllm",
 "repo_slug": "vllm-project-vllm",
 "title": "Serve several LoRA fine-tunes from one base model",
 "page_title": "How to serve several LoRA fine-tunes from one base model with vLLM",
 "summary": "Run multiple adapters on a single loaded model instead of loading a full copy for each.",
 "who": "An ML engineer who maintains several fine-tuned variants of the same base model for different customers or tasks.",
 "problem": "Loading a full model per fine-tune wastes GPU memory and makes each variant expensive to host.",
 "outcome": "One server that answers requests for each adapter by name, sharing the base model weights.",
 "steps": [
  "Install vLLM with `uv pip install vllm`.",
  "Start the server for your base model with LoRA support enabled, following the Quickstart and supported models docs. (inferred, check the README)",
  "Register each LoRA adapter path with the server as described in the official documentation. (inferred, check the README)",
  "Send one request per adapter and compare the replies to the base model's reply.",
  "Record which adapter names the server accepts."
 ],
 "agent_prompt": "Using the vllm-project/vllm repo, serve the base model <base-model-id> with the LoRA adapters at <adapter-paths>. Send the same prompt to each adapter and the base model, then report the differences. Verify that each adapter name returns a reply.",
 "agents": [
  "any"
 ],
 "difficulty": "Advanced",
 "time": "1 hour 30 minutes",
 "basis": "readme",
 "caveat": "The README confirms multi-LoRA support but not the flags or adapter registration steps, so verify those in the official docs.",
 "category": "Software and DevOps",
 "tags": [
  "Software and DevOps"
 ],
 "lang": "python",
 "requirements": [
  "Python with uv or pip installed",
  "A supported NVIDIA, AMD or Intel GPU, or an x86, ARM or PowerPC CPU",
  "A Hugging Face model you are allowed to download and use"
 ],
 "risk": "none",
 "seen_in_the_wild": false,
 "mentioned_publicly": false,
 "risks": [],
 "best": false,
 "score": 0.8,
 "evidence": [],
 "url": "https://dedupedai.com/use-cases/vllm-project-vllm/serve-lora-adapters-from-one-base-model/",
 "md": "https://dedupedai.com/use-cases/vllm-project-vllm/serve-lora-adapters-from-one-base-model/index.md",
 "disclaimer": "Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked \"Seen in the wild\", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email hello@dedupedai.com and we will look at it promptly.",
 "api": "https://dedupedai.com/api/v1/usecases/vllm-project-vllm--serve-lora-adapters-from-one-base-model.json",
 "api_version": "v1"
}