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# Use a pipeline as a high-level helper | |
from transformers import pipeline | |
import gradio as gr | |
pipe = pipeline("summarization", model="ayoubkirouane/T5-4-Summarization") | |
def summarization(text) : | |
return pipe(text)[0]["summary_text"] | |
# Create a Gradio interface | |
iface = gr.Interface( | |
fn=summarization, | |
inputs=gr.Textbox(prompt="Input Text"), | |
outputs=gr.Textbox(prompt="Generated Summary") , | |
allow_flagging=False , | |
title="T5-4-Summarization" , | |
description="This app generates a summary of the input text using T5 fine-tuned model.", | |
) | |
# Launch the Gradio app | |
iface.launch(debug=True) |