初始化项目，由ModelHub XC社区提供模型

Model: MegaScience/Qwen2.5-3B-MegaScience
Source: Original Platform

README.md

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+---
+base_model:
+- Qwen/Qwen2.5-3B
+datasets:
+- MegaScience/MegaScience
+language:
+- en
+license: apache-2.0
+metrics:
+- accuracy
+pipeline_tag: text-generation
+library_name: transformers
+---
+
+# [MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning](https://huggingface.co/papers/2507.16812)
+
+This repository contains the `Qwen2.5-3B-MegaScience` model, one of the models trained as part of the MegaScience project.
+
+For the official code, data processing pipeline, and evaluation system, please refer to the [MegaScience GitHub repository](https://github.com/GAIR-NLP/lm-open-science-evaluation).
+
+## Qwen2.5-3B-MegaScience
+
+### Usage
+
+You can use this model with the Hugging Face `transformers` library:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "MegaScience/Qwen2.5-3B-MegaScience"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Example text generation
+prompt = "The capital of France is"
+messages = [
+    {"role": "user", "content": prompt}
+]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+model_inputs = tokenizer([text], return_tensors="pt")
+
+generated_ids = model.generate(model_inputs.input_ids, max_new_tokens=20)
+print(tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0])
+```
+
+### Training Recipe
+
+- **LR**: 5e-6
+- **LR Schedule**: Cosine
+- **Batch Size**: 512
+- **Max Length**: 4,096
+- **Warm Up Ratio**: 0.05
+- **Epochs**: 3
+
+### Evaluation Results
+
+<div style="display: flex; justify-content: left; gap: 20px;">
+<img src="https://cdn-uploads.huggingface.co/production/uploads/616bfc2b40e2f69baa1c7add/abIVZ2XB9D-o-TCyvOkDE.png" alt="Data Pipeline" style="width:80%;">
+</div>
+
+<div style="display: flex; justify-content: left; gap: 20px;">
+<img src="https://cdn-uploads.huggingface.co/production/uploads/616bfc2b40e2f69baa1c7add/xFTJ7nevc3S4UYJxUS7ue.png" alt="Data Pipeline" style="width:80%;">
+</div>
+
+### More about MegaScience
+
+<div style="display: flex; justify-content: left; gap: 20px;">
+<img src="https://cdn-uploads.huggingface.co/production/uploads/616bfc2b40e2f69baa1c7add/VogIpBbjfNxXFP9DfVMms.png" alt="Data Pipeline" style="width:100%;">
+</div>
+
+## Citation
+
+Check out our [paper](https://arxiv.org/abs/2507.16812) for more details. If you use our dataset or find our work useful, please cite
+
+```
+@article{fan2025megascience,
+  title={MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning},
+  author={Fan, Run-Ze and Wang, Zengzhi and Liu, Pengfei},
+  year={2025},
+  journal={arXiv preprint arXiv:2507.16812},
+  url={https://arxiv.org/abs/2507.16812}
+}
+```