Instructions to use internlm/OREAL-32B-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use internlm/OREAL-32B-SFT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="internlm/OREAL-32B-SFT")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("internlm/OREAL-32B-SFT") model = AutoModelForCausalLM.from_pretrained("internlm/OREAL-32B-SFT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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If you find this work useful in your research, please consider citing:
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```bibtex
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@
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2502.06781},
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}
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```
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If you find this work useful in your research, please consider citing:
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```bibtex
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@article{lyu2025exploring,
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title={Exploring the Limit of Outcome Reward for Learning Mathematical Reasoning},
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author={Lyu, Chengqi and Gao, Songyang and Gu, Yuzhe and Zhang, Wenwei and Gao, Jianfei and Liu, Kuikun and Wang, Ziyi and Li, Shuaibin and Zhao, Qian and Huang, Haian and others},
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journal={arXiv preprint arXiv:2502.06781},
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year={2025}
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}
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```
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