lm-sys / lm-sys/FastChat

FastChat Code base help

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Python
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Description

Hello lm-sys team, I was looking through the code base of Fastchat for Chatbot arena code but I Couldn't find it.
I am specifically interested on the model selection when user asks a question. I have gone through your Research Paper to Understand your Elo Rankings and Active sampling of Model Selection.

It want to explore the LLM Selection using active sampling and how you are doing it.
It would be helpful if you can give more explanation or insights on it.

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Research direction

No file, test, or entry point is named. Start by locating the Chatbot Arena model-selection code in the FastChat codebase and compare it with the cited Elo Rankings and Active Sampling research paper. Done would require a concrete explanation or documentation of how active sampling selects models, but the requested scope is not defined.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
ai, machine-learning
Issue type
Documentation
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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