Create app.py

app.py

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+import torch
+import gradio as gr
+from transformers import pipeline
+
+
+
+text_summary = pipeline("summarization", model= "sshleifer/distilbart-xsum-12-6" )
+
+def summarise_txt(input):
+    output = text_summary(input)
+    return output[0]['summary_text']
+
+gr.close_all()
+demo = gr.Interface(
+    fn= summarise_txt,
+    inputs= [gr.Textbox(label="input a text to summarize in here", lines=8)],
+    outputs= [gr.Textbox(label= "text after summarization", lines= 4)],
+    title= "text summarizer project",
+    description= "the project takes a text as input and a summarized text as an output using hugging face models"
+
+)
+demo.launch()
+
+
+
+