Instructions to use openbmb/Eurus-RM-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/Eurus-RM-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="openbmb/Eurus-RM-7b", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("openbmb/Eurus-RM-7b", trust_remote_code=True) model = AutoModel.from_pretrained("openbmb/Eurus-RM-7b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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title={Advancing LLM Reasoning Generalists with Preference Trees},
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author={Lifan Yuan and Ganqu Cui and Hanbin Wang and Ning Ding and Xingyao Wang and Jia Deng and Boji Shan and Huimin Chen and Ruobing Xie and Yankai Lin and Zhenghao Liu and Bowen Zhou and Hao Peng and Zhiyuan Liu and Maosong Sun},
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year={2024},
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}
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```
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title={Advancing LLM Reasoning Generalists with Preference Trees},
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author={Lifan Yuan and Ganqu Cui and Hanbin Wang and Ning Ding and Xingyao Wang and Jia Deng and Boji Shan and Huimin Chen and Ruobing Xie and Yankai Lin and Zhenghao Liu and Bowen Zhou and Hao Peng and Zhiyuan Liu and Maosong Sun},
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year={2024},
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eprint={2404.02078},
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archivePrefix={arXiv},
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}
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```
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