Create app.py

app.py

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+import torch
+import gradio as gr
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+# downloaded the model from web
+pipe = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6",
+               torch_dtype=torch.bfloat16)
+
+# def summary(input):
+#     output = text_summary(input)
+#     return output[0]['summary_text']
+#
+#
+gr.close_all()
+
+# simple gradio web app
+# demo = gr.Interface(fn=summary, inputs="text", outputs="text")
+
+# beautified
+demo = gr.Interface(
+    fn=summary,
+    inputs=[gr.Textbox(label="Input text to summarize", lines=6)],
+    outputs=[gr.Textbox(label="Summarized text", lines=4)],
+    title="Project 01: Text Summarization",
+    description="As understood from the title, if not already, this application will summarize your text"
+)
+
+demo.launch()