Add paper and project page links to model card
#1
by nielsr HF Staff - opened
README.md
CHANGED
|
@@ -1,10 +1,10 @@
|
|
| 1 |
---
|
|
|
|
|
|
|
|
|
|
| 2 |
license: other
|
| 3 |
license_name: apache-2.0
|
| 4 |
license_link: https://huggingface.co/Qwen/Qwen2.5-Omni-7B/blob/main/LICENSE
|
| 5 |
-
language:
|
| 6 |
-
- en
|
| 7 |
-
base_model: Qwen/Qwen2.5-Omni-7B
|
| 8 |
pipeline_tag: audio-text-to-text
|
| 9 |
tags:
|
| 10 |
- audio
|
|
@@ -14,8 +14,9 @@ tags:
|
|
| 14 |
|
| 15 |
# AudioRubrics
|
| 16 |
|
| 17 |
-
The model from
|
| 18 |
|
|
|
|
| 19 |
- Code: https://github.com/Yu-Fangxu/AudioRubrics
|
| 20 |
- Rubric dataset: https://huggingface.co/datasets/umd-zhou-lab/AVQA-Audio-Rubrics
|
| 21 |
|
|
@@ -26,4 +27,4 @@ vllm serve umd-zhou-lab/AudioRubrics --served-model-name omni --trust-remote-cod
|
|
| 26 |
--max-model-len 8192 --limit-mm-per-prompt '{"audio":1}'
|
| 27 |
```
|
| 28 |
|
| 29 |
-
See the [GitHub repository](https://github.com/Yu-Fangxu/AudioRubrics) for training and evaluation instructions.
|
|
|
|
| 1 |
---
|
| 2 |
+
base_model: Qwen/Qwen2.5-Omni-7B
|
| 3 |
+
language:
|
| 4 |
+
- en
|
| 5 |
license: other
|
| 6 |
license_name: apache-2.0
|
| 7 |
license_link: https://huggingface.co/Qwen/Qwen2.5-Omni-7B/blob/main/LICENSE
|
|
|
|
|
|
|
|
|
|
| 8 |
pipeline_tag: audio-text-to-text
|
| 9 |
tags:
|
| 10 |
- audio
|
|
|
|
| 14 |
|
| 15 |
# AudioRubrics
|
| 16 |
|
| 17 |
+
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.
|
| 18 |
|
| 19 |
+
- Project page: https://audiorubrics.github.io
|
| 20 |
- Code: https://github.com/Yu-Fangxu/AudioRubrics
|
| 21 |
- Rubric dataset: https://huggingface.co/datasets/umd-zhou-lab/AVQA-Audio-Rubrics
|
| 22 |
|
|
|
|
| 27 |
--max-model-len 8192 --limit-mm-per-prompt '{"audio":1}'
|
| 28 |
```
|
| 29 |
|
| 30 |
+
See the [GitHub repository](https://github.com/Yu-Fangxu/AudioRubrics) for training and evaluation instructions.
|