Instructions to use nlpie/tiny-biobert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpie/tiny-biobert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nlpie/tiny-biobert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nlpie/tiny-biobert") model = AutoModelForMaskedLM.from_pretrained("nlpie/tiny-biobert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86a37c2154ff9c4c1603397d7bce9a43ab0905dd484ff57628d6a69e265dffaa
- Size of remote file:
- 55.6 MB
- SHA256:
- 6845bb1a1a27b9452e63bc139c015d7924ec7549cbec2aa308e714e735b335fc
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