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| #packages | |
| import gradio as gr | |
| import torch | |
| from transformers import pipeline | |
| #%% Text Summarization | |
| pipe = pipeline("summarization", model="Falconsai/text_summarization") | |
| def summarize(text): | |
| result = pipe(text, min_length=5, max_length=20) | |
| return result[0]['summary_text'] | |
| title = "Text Summarization" | |
| description = "This model summarizes an article (using Falconsai/text_summarization model)" | |
| gr.Interface(fn=summarize, inputs="text", outputs="text", title=title, description=description).launch() | |