Improve model card and add metadata (#1)

- Improve model card and add metadata (1a1049ca6b0445e4731c2697a6fc1954b2717577)


Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

README.md

@@ -1,9 +1,34 @@
 ---
 license: apache-2.0
+library_name: transformers
+pipeline_tag: image-text-to-text
+base_model: Qwen/Qwen2.5-VL-7B-Instruct
+tags:
+- multimodal
+- agent
+- reinforcement-learning
+- qwen
 ---
+
+# PyVision-Image-7B-RL
+
 [PyVision-RL: Forging Open Agentic Vision Models via RL](https://arxiv.org/abs/2602.20739)
 
-This is PyVision-Image-7B-RL, post trained from Qwen2.5-VL-7B.
+This is **PyVision-Image-7B-RL**, a multimodal agentic vision model post-trained from [Qwen2.5-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-VL-7B-Instruct) using the PyVision-RL reinforcement learning framework.
+
+- **Project Page:** [https://agent-x.space/pyvision-rl/](https://agent-x.space/pyvision-rl/)
+- **Repository:** [https://github.com/agents-x-project/PyVision-RL](https://github.com/agents-x-project/PyVision-RL)
+- **Paper:** [https://arxiv.org/abs/2602.20739](https://arxiv.org/abs/2602.20739)
+
+## Description
+
+Reinforcement learning for agentic multimodal models often suffers from "interaction collapse," where models learn to reduce tool usage and multi-turn reasoning. PyVision-RL is a framework designed to stabilize training and sustain interaction using an oversampling-filtering-ranking rollout strategy combined with an accumulative tool reward. 
+
+PyVision-Image-7B-RL is specifically optimized for image understanding tasks and sustained multi-turn tool interaction, demonstrating strong performance and efficiency for scalable multimodal agents.
+
+## Citation
+
+If you find this work useful, please cite the following paper:
 
 ```bibtex
 @article{pyvisionrl2026,