created app.py

app.py

@@ -0,0 +1,14 @@
+from transformers import PegasusForConditionalGeneration, PegasusTokenizer
+import gradio as gr
+
+model_name = "ailm/pegasus-samsum-model"
+model = PegasusForConditionalGeneration.from_pretrained(model_name)
+tokenizer = PegasusTokenizer.from_pretrained(f"{model_name}/tokenizer")
+
+def summarize(text):
+    tokens = tokenizer(text, truncation=True, padding="longest", return_tensors="pt")
+    summary = model.generate(**tokens)
+    return tokenizer.decode(summary[0], skip_special_tokens=True)
+
+iface = gr.Interface(fn=summarize, inputs="text", outputs="text")
+iface.launch()