Instructions to use nlpie/distil-biobert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpie/distil-biobert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nlpie/distil-biobert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nlpie/distil-biobert") model = AutoModelForMaskedLM.from_pretrained("nlpie/distil-biobert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a35bd9df2992833960c79c2207eb0b5b932fd389a7971b5e17ffbdfd50328958
- Size of remote file:
- 263 MB
- SHA256:
- fa06fecbb1bea9f082f25688f4fcf85f7ea8f92e462b8683a022bd6f71fa63e3
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