| 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(label="Input Text"), | |
| outputs=gr.Textbox(label="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) | |