Instructions to use fspanda/Medical-Bio-BERT2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fspanda/Medical-Bio-BERT2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="fspanda/Medical-Bio-BERT2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("fspanda/Medical-Bio-BERT2") model = AutoModelForMaskedLM.from_pretrained("fspanda/Medical-Bio-BERT2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d963cd596333361a60db82f87783c220f46d6743f2f989b940280c841cf77af3
- Size of remote file:
- 359 MB
- SHA256:
- 60dbbb713af54c46c66f9c13b6534220471a1f7808bd18732b5dc0d3a22ed787
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