Instructions to use allenai/scibert_scivocab_uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/scibert_scivocab_uncased with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("allenai/scibert_scivocab_uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from allenai/scibert_scivocab_uncased: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/allenai/scibert_scivocab_uncased/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://allenai/scibert_scivocab_uncased/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/allenai/scibert_scivocab_uncased/resolve/main/flax_model.msgpack
440 MB
- Xet hash:
- e4cf1958a581c462d917673d4e892113cb0583c544f7db909236ecc5149cdaf3
- Size of remote file:
- 440 MB
- SHA256:
- 53d32c1d93bebe3fbc0a20e081d8575defc8d481989f97fb82c0f95f3b38f2c1
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