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Model: IIGroup/X-Coder-RL-Qwen2.5-7B
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model:
+  - IIGroup/X-Coder-SFT-Qwen2.5-7B
+datasets:
+  - IIGroup/X-Coder-RL-40k
+language:
+  - en
+tags:
+  - code
+  - rl
+  - competitive-programming
+---
+
+# X-Coder-RL-Qwen2.5-7B
+
+X-Coder-RL-Qwen2.5-7B is a strong code reasoning foundation model trained with RLVR on fully synthetic rl data, achieving strong reasoning performance on competitive programming.
+
+## Model Description
+
+- **Base Model**: [IIGroup/X-Coder-SFT-Qwen2.5-7B](https://huggingface.co/IIGroup/X-Coder-SFT-Qwen2.5-7B) 
+- **Training Method**: GRPO
+- **Training Data**: [IIGroup/X-Coder-RL-40k](https://huggingface.co/datasets/IIGroup/X-Coder-RL-40k)
+- **Parameters**: 7B
+
+## Training
+
+This model was trained using the X-Coder RLVR framework. For training details and code, please refer to the [X-Coder GitHub repository](https://github.com/JieWu02/X-Coder).
+
+## Performance
+
+**Performance on LiveCodeBench v5.**
+
+![Results](results.png)
+
+## Recommended Inference Parameters
+
+| Parameter | Value |
+|-----------|-------|
+| temperature | 0.6 |
+| top_p | 0.95 |
+| top_k | 20 (or -1 to disable) |
+| max_new_tokens | 32768 |
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "IIGroup/X-Coder-RL-Qwen2.5-7B"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto")
+
+prompt = "Write a Python function to solve the two sum problem."
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=32768,
+    temperature=0.6,
+    top_p=0.95,
+    top_k=20,
+    do_sample=True
+)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Citation
+
+```bibtex
+@misc{wu2026xcoderadvancingcompetitiveprogramming,
+      title={X-Coder: Advancing Competitive Programming with Fully Synthetic Tasks, Solutions, and Tests}, 
+      author={Jie Wu and Haoling Li and Xin Zhang and Jiani Guo and Jane Luo and Steven Liu and Yangyu Huang and Ruihang Chu and Scarlett Li and Yujiu Yang},
+      year={2026},
+      eprint={2601.06953},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2601.06953}, 
+}
+```
+
+## License
+
+This project is licensed under the Apache License 2.0.