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)# 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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datasets:
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- openbmb/UltraFeedback
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- openbmb/UltraInteract_pair
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tags:
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- reward_model
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pipeline_tag: text-classification
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datasets:
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- openbmb/UltraFeedback
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- openbmb/UltraInteract_pair
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- openbmb/UltraSafety
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tags:
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- reward_model
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pipeline_tag: text-classification
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