Instructions to use osunlp/BioVocabBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osunlp/BioVocabBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="osunlp/BioVocabBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("osunlp/BioVocabBERT") model = AutoModelForMaskedLM.from_pretrained("osunlp/BioVocabBERT") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aeb00afb1c7a303aff3434ba2cad7c25efc31a01fc7190f4f451721e4a85f7ae
- Size of remote file:
- 591 MB
- SHA256:
- c551ab2271480695f27e196ada689052aaee02576bc4da6c4efb4ff2837df398
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