lm-sys / lm-sys/FastChat

directly use base model when using LoRA for serving

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Python
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Description

Can the base model be directly accessed when using LoRA for serving? This is because fine-tuning leads to the loss of some capabilities, necessitating the use of base model inference.
What should I do. Plz help me.

Contributor guide

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No file, test, or entry point is identified in the issue. Start by locating the LoRA serving path and clarifying how base-model inference should be selected; done requires an agreed behavior and corresponding implementation or usage guidance.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
ai, backend
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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