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# -*- coding: utf-8 -*-
"""Question_Answering_Gradio.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/12ga045iO8c2vMqYZQY4zPttnEv8dIUZe
"""
from transformers import pipeline
from transformers import AutoModelForQuestionAnswering
from transformers import AutoTokenizer
model_checkpoint = "Madhana/distilroberta-base-finetuned-wikitext2-SQuAD-qa-WandB2"
new_model = AutoModelForQuestionAnswering.from_pretrained(model_checkpoint)
tokenizer = AutoTokenizer.from_pretrained("distilroberta-base", use_fast=True)
qa = pipeline("question-answering", new_model, tokenizer, tokenizer)
import gradio as gr
demo = gr.Blocks()
with demo:
gr.Markdown("Language Model QA Demo")
with gr.Tabs():
with gr.TabItem("Question Answering"):
with gr.Row():
qa_input = gr.Textbox(label = "Input Text")
qa_context = gr.Textbox(label = "Input Context")
qa_output = gr.Textbox(label = "Output")
qa_button = gr.Button("Answer")
qa_button.click(qa, inputs=[qa_input, qa_context], outputs=qa_output)
demo.launch() # share=True |