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
Download misc/intro.jpeg from internlm/POLAR-7B: direct link, hf CLI and curl.
- Browser
- Download file 2.3 MB
-
https://huggingface.co/internlm/POLAR-7B/resolve/main/misc/intro.jpeg
- Command line
-
hf download hf://internlm/POLAR-7B/misc/intro.jpeg
-
curl -L -o intro.jpeg https://huggingface.co/internlm/POLAR-7B/resolve/main/misc/intro.jpeg
2.3 MB

- Xet hash:
- c78cc9e6ba0667078258d339f64e324d5be3de10b0bc25c85c57fbef246ccc21
- Size of remote file:
- 2.3 MB
- SHA256:
- d81fdc6c6f832d3859279549a3443eed5cf819a868d9d6c821c10928bb0ba022
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