---
base_model: Qwen/Qwen2.5-Omni-7B
language:
- en
license: other
license_name: apache-2.0
license_link: https://huggingface.co/Qwen/Qwen2.5-Omni-7B/blob/main/LICENSE
pipeline_tag: audio-text-to-text
tags:
- audio
- audio-reasoning
- reinforcement-learning
---

# AudioRubrics

The model from [Reinforcement Learning with Evolving Rubrics as Rewards for Audio Reasoning](https://huggingface.co/papers/2608.02831): Qwen2.5-Omni-7B post-trained with GRPO using self-evolving, audio-grounded rubric rewards and an overthinking penalty.

- Project page: https://audiorubrics.github.io
- Code: https://github.com/tianyi-lab/AudioRubrics
- Rubric dataset: https://huggingface.co/datasets/umd-zhou-lab/AVQA-Audio-Rubrics

This is the full merged checkpoint (thinker merged back into the complete Omni model) and can be served directly with vLLM:

```bash
vllm serve umd-zhou-lab/AudioRubrics --served-model-name omni --trust-remote-code \
  --max-model-len 8192 --limit-mm-per-prompt '{"audio":1}'
```

See the [GitHub repository](https://github.com/Yu-Fangxu/AudioRubrics) for training and evaluation instructions.