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
Add pipeline tag and library name to metadata
#2
by nielsr HF Staff - opened
This PR enhances the model card by adding the pipeline_tag: text-ranking and library_name: transformers to the YAML metadata. This improves the model's discoverability on the Hub by allowing users to filter by the "text-ranking" pipeline and enables the "Load with Transformers" widget for easier programmatic access.
RowitZou changed pull request status to merged