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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 632e602ab7097d39551c96b28f3bf005337df0f437fb6eec902a5678128f8535
- Size of remote file:
- 440 MB
- SHA256:
- d513412d396cecec5f67936ac871b4aaf1178dfb5193776e790fd2b28bba240c
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