Instructions to use microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract") model = AutoModelForMaskedLM.from_pretrained("microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Update release note for clarity
Browse files
README.md
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* This model was previously named **"PubMedBERT (abstracts)"**.
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* You can either adopt the new model name "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract" or update your transformers library to version 4.22+ if you
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<div style="border: 2px solid orange; border-radius:10px; padding:0px 10px; width: fit-content;">
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* This model was previously named **"PubMedBERT (abstracts)"**.
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* You can either adopt the new model name "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract" or update your `transformers` library to version 4.22+ if you need to refer to the old name.
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