Instructions to use yonghyeon/biochem_scibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yonghyeon/biochem_scibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="yonghyeon/biochem_scibert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("yonghyeon/biochem_scibert") model = AutoModelForMaskedLM.from_pretrained("yonghyeon/biochem_scibert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from yonghyeon/biochem_scibert: direct link, hf CLI and curl.
- Browser
- Download file 566 MB
-
https://huggingface.co/yonghyeon/biochem_scibert/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://yonghyeon/biochem_scibert/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/yonghyeon/biochem_scibert/resolve/main/pytorch_model.bin
566 MB
- Xet hash:
- 83e6ef96dc5dc89614bbb69c6db57e71827d4842845c39999183a4d8d7384674
- Size of remote file:
- 566 MB
- SHA256:
- aba63ef337d8202c36f001be0fffac567c22d9d33ec4bffe633655a14b80067a
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