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README.md
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The model was trained on a combined maccrobat and i2c2 dataset and is based on biobert. If you use this model kindly cite the paper below:
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<b> <u> How to use the Model </u> </b>
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nlp = spacy.load("en_biobert_ner_symptom")
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for ent in doc.ents:
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print(ent)
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</div>
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### Accuracy
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## Model Description
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The model was trained on a combined maccrobat and i2c2 dataset and is based on biobert. If you use this model kindly cite the paper below:
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<b> <u> How to use the Model </u> </b>
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## Model Usage
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The model can be used as a spacy library.
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```python
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>>> !pip install https://huggingface.co/pmaitra/en_biobert_ner_symptom/resolve/main/en_biobert_ner_symptom-any-py3-none-any.whl
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>>> import spacy
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>>> nlp = spacy.load("en_biobert_ner_symptom")
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>>> doc = nlp("He complained of dizziness and nausea during the Iowa trip.")
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>>> for ent in doc.ents: print(ent)
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```
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### Accuracy
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