Text Classification
Transformers
PyTorch
English
Chinese
internlm2
feature-extraction
Reward
RL
RFT
Reward Model
custom_code
Instructions to use internlm/POLAR-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use internlm/POLAR-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="internlm/POLAR-7B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("internlm/POLAR-7B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Update pipeline tag
Verified signatureIt looks like the POLAR models accidentally got the "text-ranking" tag, but that only applies to rerankers (cross-encoders), not to reward models. Would be great to update the other models too!32416cd
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Add pipeline tag and library name to metadata (#2)
Verified signature- Add pipeline tag and library name to metadata (55cb02eb834550f0fef62f019b4951e33b641fab) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>af82088 -
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