lm-sys / lm-sys/FastChat

Eval request https://huggingface.co/rfcoder0/qwen3-4b-custom-Sile

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Dominant language
Python
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Description

I’d like to request evaluation of a new Hugging Face model:
👉 https://huggingface.co/rfcoder0/qwen3-4b-custom-Sile
• Model size: 4B parameters
• Training hardware: RTX 3060 + RTX 3070 (consumer GPUs)
• Performance: Rivals Qwen-3 8B
• Intended use: General-purpose chat / instruct

This is a custom 4B model designed to show that high performance is possible with modest hardware. Would be great to see it included in your evaluation sweeps/leaderboards for comparison.

Thank you!

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Research direction

Start by locating FastChat’s evaluation sweep and leaderboard entry points, then review how Hugging Face models are registered for comparison runs. Done means the requested rfcoder0/qwen3-4b-custom-Sile model is evaluated through the relevant workflow and its results are included in the appropriate comparison output.

Written by the indexing model from the issue text.

Assessment

Tech stack
huggingface, python
Domain
machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
30/100

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