initial

app.py

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+import gradio as gr
+from transformers import pipeline
+
+# Initialize the model
+model = pipeline("summarization", model="luisotorres/bart-finetuned-samsum")
+
+def summarize_text(text):
+    try:
+        summary = model(text, max_length=130, min_length=30)
+        return summary[0]["summary_text"]
+    except Exception as e:
+        return str(e)
+
+# Create Gradio interface
+iface = gr.Interface(
+    fn=summarize_text,
+    inputs=gr.Textbox(label="Input Text", lines=5),
+    outputs=gr.Textbox(label="Summary"),
+    title="Text Summarization",
+    description="Enter your text to generate a summary.",
+    examples=[
+        ["Sarah: Do you think it's a good idea to invest in Bitcoin?\nEmily: I'm skeptical. The market is very volatile, and you could lose money.\nSarah: True. But there's also a high upside, right?"]
+    ]
+)
+
+# Launch the interface
+iface.launch()

requirements.txt

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+gradio
+transformers
+torch