Upload 2 files

app.py

@@ -0,0 +1,14 @@
+from transformers import PegasusForConditionalGeneration, PegasusTokenizer
+import gradio as grad
+mdl_name = "google/pegasus-xsum"
+pegasus_tkn = PegasusTokenizer.from_pretrained(mdl_name)
+mdl = PegasusForConditionalGeneration.from_pretrained(mdl_name)
+
+def summarize(text):
+    tokens = pegasus_tkn(text, truncation=True, padding="longest", return_tensors="pt")
+    translated_txt = mdl.generate(**tokens,num_return_sequences=5,max_length=200,temperature=1.5,num_beams=10)
+    response = pegasus_tkn.batch_decode(translated_txt, skip_special_tokens=True)
+    return response
+txt=grad.Textbox(lines=10, label="English", placeholder="English Text here")
+out=grad.Textbox(lines=10, label="Summary")
+grad.Interface(summarize, inputs=txt, outputs=out).launch()

requirements.txt

@@ -0,0 +1,4 @@
+gradio
+transformers
+torch
+transformers[sentencepiece]