Instructions to use squeezebert/squeezebert-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use squeezebert/squeezebert-mnli with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("squeezebert/squeezebert-mnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from squeezebert/squeezebert-mnli: direct link, hf CLI and curl.
- Browser
- Download file 204 MB
-
https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://squeezebert/squeezebert-mnli/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/pytorch_model.bin
204 MB
- Xet hash:
- b47ee48338e7742aed46b99e2320417ad9b207a00ef485e79c95f641e37da13c
- Size of remote file:
- 204 MB
- SHA256:
- 1b283a8fd86b1916f18e52a9031f39353d43906b9bbe659edfd452f60b69f4e9
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