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import gradio as gr | |
from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline | |
model_name = "IProject-10/roberta-base-finetuned-squad2" | |
nlp = pipeline("question-answering", model=model_name, tokenizer=model_name) | |
def predict(context, question): | |
res = nlp({"question": question, "context": context}) | |
return res["answer"] | |
md = """ | |
""" | |
context = "The Amazon rainforest, also known in English as Amazonia or the Amazon Jungle, is a moist broadleaf forest that covers most of the Amazon basin of South America..." | |
question = "Which continent is the Amazon rainforest in?" | |
gr.Interface( | |
predict, | |
inputs=[ | |
gr.Textbox(lines=7, value=context, label="Context Paragraph"), | |
gr.Textbox(lines=2, value=question, label="Question"), | |
], | |
outputs=gr.Textbox(label="Answer"), | |
title="Question Answering System", | |
description=md, | |
).launch() | |