Instructions to use GeneZC/sparsebert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GeneZC/sparsebert-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, SparseBertHidden tokenizer = AutoTokenizer.from_pretrained("GeneZC/sparsebert-base") model = SparseBertHidden.from_pretrained("GeneZC/sparsebert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from GeneZC/sparsebert-base: direct link, hf CLI and curl.
- Browser
- Download file 441 MB
-
https://huggingface.co/GeneZC/sparsebert-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://GeneZC/sparsebert-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/GeneZC/sparsebert-base/resolve/main/pytorch_model.bin
441 MB
- Xet hash:
- 0571742a46e4dbf180a5935fb8b1410b2e813fcc0a357fa6292e8e4931a7397c
- Size of remote file:
- 441 MB
- SHA256:
- 56a41b64b6df1ddee8da268b5f67b714ef3b198e9eee1c97b1d0fb0b067684ce
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