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| import gradio as gr | |
| from transformers import pipeline | |
| def summarize_aritcle(Article, model_selector, min_length, max_length): | |
| summarizer = pipeline("summarization", model=model_selector) | |
| return f"{model_selector}: \n {summarizer(Article, max_length=max_length, min_length=min_length, do_sample=False)[0]['summary_text']}" | |
| # gradio_app = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| model_list = ["facebook/bart-large-cnn", "facebook/bart-large-xsum"] | |
| with gr.Blocks() as demo: | |
| model_selector = gr.Dropdown(model_list, label="model selection", value=0, show_label=True) | |
| article = gr.TextArea(label="Article Text") | |
| min_length=gr.Number(label="min summary length", value=30) | |
| max_length=gr.Number(label="max summary length", value=100) | |
| summary_text = gr.TextArea(label="Summary Text") | |
| run_btn = gr.Button("Do Summarize") | |
| run_btn.click(fn=summarize_aritcle, inputs=[article, model_selector, min_length, max_length], outputs=summary_text) | |
| if __name__ == "__main__": | |
| demo.launch() |