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
- Xet hash:
- b80ca096b4a199da8abc026f479844d1a8cd935dae8619451bdcc8c38bd7aa81
- Size of remote file:
- 440 MB
- SHA256:
- b1888456f3d6bb96c8d3c08d974526fa69e5578b73e235227d1d42568926f640
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