Create app.py

app.py

@@ -0,0 +1,14 @@
+import gradio as gr
+from transformers import PegasusForConditionalGeneration
+from transformers import PegasusTokenizer
+from transformers import pipeline
+
+model_name = "google/pegasus-xsum"
+pegasus_tokenizer = PegasusTokenizer.from_pretrained(model_name)
+def summarize(input_text):
+  nwords=len(input_text.split(" "))
+  # Define summarization pipeline 
+  summarizer = pipeline("summarization", model=model_name, tokenizer=pegasus_tokenizer,min_length=int(nwords/10)+20, max_length=int(nwords/5+20), framework="pt")
+  summary=summarizer(input_text)[0]['summary_text']
+  return(summary)
+gr.Interface(fn=summarize,inputs="textbox",outputs="textbox").launch(share="True");