| from transformers import pipeline | |
| import gradio as gr | |
| import torch | |
| def textSummarizer(ARTICLE,MaxTokens,MinTokens): | |
| summarizer = pipeline("summarization", model="facebook/bart-large-cnn") | |
| result = summarizer(ARTICLE, max_length=MaxTokens, min_length=MinTokens, do_sample=False) | |
| return result[0]["summary_text"] | |
| app = gr.Interface(textSummarizer, | |
| inputs = [gr.Textbox(), | |
| gr.Slider(minimum=0,maximum=500,step=2), | |
| gr.Slider(minimum=0,maximum=100,step=1)], | |
| outputs = gr.Textbox(), | |
| title = "Article Summarizer", | |
| theme=gr.themes.Soft()) | |
| app.launch() |