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import subprocess | |
# Install transformers library | |
subprocess.check_call(["pip", "install", "transformers"]) | |
subprocess.check_call(["pip", "install", "torch"]) | |
import gradio as gr | |
from transformers import pipeline | |
# Replace this with your own checkpoint | |
model_checkpoint = "huggingface-course/bert-finetuned-squad" | |
question_answerer = pipeline("question-answering", model=model_checkpoint) | |
def answer_question(question, context): | |
answer = question_answerer(question=question, context=context) | |
return answer['answer'], answer['score'], answer['start'], answer['end'] | |
iface = gr.Interface( | |
fn=answer_question, | |
inputs=["text", "text"], | |
outputs=["text", "number", "number", "number"], | |
title="Extractive Question Answering" | |
) | |
iface.launch() | |