base code

app.py

@@ -0,0 +1,23 @@
+import gradio as gr
+
+from transformers import BartForConditionalGeneration, BartTokenizer, pipeline
+
+# Load the model and tokenizer using the authentication token
+model = BartForConditionalGeneration.from_pretrained("sshleifer/distilbart-cnn-12-6")
+tokenizer = BartTokenizer.from_pretrained("sshleifer/distilbart-cnn-12-6")
+
+# Create the summarization pipeline with the loaded model and tokenizer
+get_completion = pipeline("summarization", model=model, tokenizer=tokenizer)
+
+def summarize(input):
+    output = get_completion(input)
+    return output[0]['summary_text']
+
+demo = gr.Interface(fn=summarize,
+                    inputs=[gr.Textbox(label="Text to summarize", lines=6)],
+                    outputs=[gr.Textbox(label="Result", lines=3)],
+                    title="Text summarization with distilbart-cnn",
+                    description="Summarize any text using the `shleifer/distilbart-cnn-12-6` model under the hood!"
+                   )
+
+demo.launch(inline=False)