Text Classification
Transformers
PyTorch
English
Chinese
internlm2
feature-extraction
Reward
RL
RFT
Reward Model
custom_code
Instructions to use internlm/POLAR-1_8B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use internlm/POLAR-1_8B-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="internlm/POLAR-1_8B-Base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("internlm/POLAR-1_8B-Base", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add pipeline_tag, library_name, and paper abstract to model card
#1
by nielsr HF Staff - opened
This PR improves the model card by adding the pipeline_tag: text-ranking and library_name: transformers to the metadata. This will enhance discoverability on the Hugging Face Hub (e.g., at https://huggingface.co/models?pipeline_tag=text-ranking) and enable the "how to use" widget for Transformers models.
Additionally, the paper abstract has been added to provide more comprehensive information about the model's purpose and methodology.
RowitZou changed pull request status to merged