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| # Import transformers pipeline | |
| from transformers import pipeline | |
| # Instantiate the pipeline with the summarization parameter and `facebook/bart-large-cnn` model. | |
| summarizer = pipeline("summarization", model="facebook/bart-large-cnn") | |
| # Import Gradio | |
| import gradio as gr | |
| # Create a summary function passing in the desired parameters | |
| def summarize(article, slider, sample): | |
| return f'{summarizer(article, max_length=slider, min_length=30, do_sample=sample)[0]["summary_text"]}' | |
| # Create a slider and checkbox instance | |
| slider = gr.Slider(50, 200, value=50, label="Number", info="Choose between a 50 and 200 word summary.") | |
| sample = gr.Checkbox(label="Do sample") | |
| # Create the checkbox component and specify a label | |
| # Update the Interface function to contain the correct parameters | |
| app = gr.Interface(fn=summarize, inputs=["text", slider, sample], outputs="text") | |
| app.launch() |