Instructions to use sagteam/pharm-relation-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sagteam/pharm-relation-extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sagteam/pharm-relation-extraction")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sagteam/pharm-relation-extraction") model = AutoModelForSequenceClassification.from_pretrained("sagteam/pharm-relation-extraction") - Notebooks
- Google Colab
- Kaggle
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pharm-relation-extraction
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pharm-relation-extraction
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Model trained to recognize 4 types of relationships between significant pharmacological entities in russian-language reviews: ADR–Drugname, Drugname–Diseasename, Drugname–SourceInfoDrug, Diseasename–Indication. The input of the model is a review text and a pair of entities, between which it is required to determine the fact of a relationship and one of the 4 types of relationship, listed above.
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