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How to Get Started With the Model

Example of single-label classification:

!pip install -U transformers

from transformers import pipeline
classifier = pipeline('text-classification', model= 'piyush23111991/bert-base-uncased-symptom-to-disease-prediction')
classifier(['I am experiencing too many cramps in the last couple of days. I think something is not right. I believe there is a small bruise on my calves, but I am not sure about it.'])
#[{'label': 'Varicose Veins', 'score': 0.5619356632232666}]

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Safetensors

Model size

110M params

Tensor type

F32

Inference Examples

Text Classification

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Model tree for piyush23111991/bert-base-uncased-symptom-to-disease-prediction

Base model

google-bert/bert-base-uncased

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piyush23111991
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bert-base-uncased-symptom-to-disease-prediction

You need to agree to share your contact information to access this model

How to Get Started With the Model

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