初始化项目，由ModelHub XC社区提供模型

Model: SantiagoC/palindrome-curriculum-v2
Source: Original Platform

README.md

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+---
+base_model: SantiagoC/palindrome-sft-qwen3
+library_name: transformers
+model_name: palindrome-curriculum-v2
+tags:
+- generated_from_trainer
+- grpo
+- trackio:https://huggingface.co/spaces/SantiagoC/palindrome-curriculum-static-3736fc
+- hf_jobs
+- trackio
+- trl
+- ml-intern
+licence: license
+---
+
+# Model Card for palindrome-curriculum-v2
+
+This model is a fine-tuned version of [SantiagoC/palindrome-sft-qwen3](https://huggingface.co/SantiagoC/palindrome-sft-qwen3).
+It has been trained using [TRL](https://github.com/huggingface/trl).
+
+## Quick start
+
+```python
+from transformers import pipeline
+
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="SantiagoC/palindrome-curriculum-v2", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+ 
+
+
+
+This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300).
+
+### Framework versions
+
+- TRL: 1.3.0
+- Transformers: 5.8.0
+- Pytorch: 2.11.0
+- Datasets: 4.8.5
+- Tokenizers: 0.22.2
+
+## Citations
+
+Cite GRPO as:
+
+```bibtex
+@article{shao2024deepseekmath,
+    title        = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},
+    author       = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},
+    year         = 2024,
+    eprint       = {arXiv:2402.03300},
+}
+```
+
+Cite TRL as:
+    
+```bibtex
+@software{vonwerra2020trl,
+  title   = {{TRL: Transformers Reinforcement Learning}},
+  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
+  license = {Apache-2.0},
+  url     = {https://github.com/huggingface/trl},
+  year    = {2020}
+}
+```
+
+<!-- ml-intern-provenance -->
+## Generated by ML Intern
+
+This model repository was generated by [ML Intern](https://github.com/huggingface/ml-intern), an agent for machine learning research and development on the Hugging Face Hub.
+
+- Try ML Intern: https://smolagents-ml-intern.hf.space
+- Source code: https://github.com/huggingface/ml-intern
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = 'SantiagoC/palindrome-curriculum-v2'
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+```
+
+For non-causal architectures, replace `AutoModelForCausalLM` with the appropriate `AutoModel` class.