Instructions to use JacopoBandoni/BioBertRelationGenesDiseases with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JacopoBandoni/BioBertRelationGenesDiseases with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JacopoBandoni/BioBertRelationGenesDiseases")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JacopoBandoni/BioBertRelationGenesDiseases") model = AutoModelForSequenceClassification.from_pretrained("JacopoBandoni/BioBertRelationGenesDiseases") - Notebooks
- Google Colab
- Kaggle
The following is a fine-tuning of the BioBert models on the GAD dataset.
The model works by masking the gene string with "@GENE$" and the disease string with "@DISEASE$".
The output is a text classification that can either be:
- "LABEL0" if there is no relation
- "LABEL1" if there is a relation.
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