Instructions to use minhpqn/bio_roberta-base_pubmed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minhpqn/bio_roberta-base_pubmed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="minhpqn/bio_roberta-base_pubmed")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("minhpqn/bio_roberta-base_pubmed") model = AutoModelForMaskedLM.from_pretrained("minhpqn/bio_roberta-base_pubmed") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72926fdb238f09a1259c35550d4ce4c3d71b274dea234d7775187ae18e571088
- Size of remote file:
- 499 MB
- SHA256:
- 5c7876b6b9e55b9a9b4e730a45f4f4baa0cf9648bc0917883d9b4c5ca70a25c4
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