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import gradio as gr | |
from transformers import pipeline | |
qa_model = pipeline("question-answering",'a-ware/bart-squadv2') | |
def fetch_answer(question, context ): | |
return qa_model(question = question, context = context)['answer'] | |
demo = gr.Interface( | |
fn=fetch_answer, | |
#take input as real time audio and use OPENAPI whisper for S2T | |
inputs=[gr.Textbox(lines=2, placeholder="What is age of patient..."), | |
gr.Textbox(lines=2, placeholder="The patient is a 71 year old male...")], | |
outputs="text", | |
examples=[['questiontest1','context1'],['questiontest2','context2']] | |
) | |
demo.launch() | |