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import gradio as gr | |
from transformers import pipeline | |
pipeline = pipeline(task="question-answering",model="Intel/bert-base-uncased-squadv1.1-sparse-80-1x4-block-pruneofa") | |
def greet(name): | |
return "Hello " + name + "!!" | |
def predict(text): | |
predictions = pipeline(text) | |
return predictions | |
md = """ | |
App coming soon! | |
Based on the [Prune Once for All: Sparse Pre-Trained Language Models](https://arxiv.org/abs/2111.05754) paper. | |
""" | |
iface = gr.Interface( | |
fn=predict, | |
inputs="text", | |
outputs="text", | |
title = "Question & Answer with Sparse BERT using the SQuAD dataset", | |
description = md | |
) | |
iface.launch() | |