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)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("internlm/POLAR-7B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update pipeline tag
#6
by nielsr HF Staff - opened
It 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!
RowitZou changed pull request status to merged