Update app.py

app.py

@@ -39,25 +39,42 @@
 # grad.Interface(translate, inputs=txt, outputs=out).launch()
 
 ################################5-6
-from transformers import AutoModel,AutoTokenizer,AutoModelForSeq2SeqLM
+# from transformers import AutoModel,AutoTokenizer,AutoModelForSeq2SeqLM
+# import gradio as grad
+# mdl_name = "Helsinki-NLP/opus-mt-en-fr"
+# mdl = AutoModelForSeq2SeqLM.from_pretrained(mdl_name)
+# my_tkn = AutoTokenizer.from_pretrained(mdl_name)
+
+# #opus_translator = pipeline("translation", model=mdl_name)
+
+# def translate(text):
+#     inputs = my_tkn(text, return_tensors="pt")
+#     trans_output = mdl.generate(**inputs)
+#     response = my_tkn.decode(trans_output[0], skip_special_tokens=True)
+
+#     #response = opus_translator(text)
+#     return response
+# txt=grad.Textbox(lines=1, label="English", placeholder="English Text here")
+# out=grad.Textbox(lines=1, label="French")
+# grad.Interface(translate, inputs=txt, outputs=out).launch()
+
+from transformers import PegasusForConditionalGeneration, PegasusTokenizer
 import gradio as grad
-mdl_name = "Helsinki-NLP/opus-mt-en-fr"
-mdl = AutoModelForSeq2SeqLM.from_pretrained(mdl_name)
-my_tkn = AutoTokenizer.from_pretrained(mdl_name)
+mdl_name = "google/pegasus-xsum"
+pegasus_tkn = PegasusTokenizer.from_pretrained(mdl_name)
+mdl = PegasusForConditionalGeneration.from_pretrained(mdl_name)
 
-#opus_translator = pipeline("translation", model=mdl_name)
 
-def translate(text):
-    inputs = my_tkn(text, return_tensors="pt")
-    trans_output = mdl.generate(**inputs)
-    response = my_tkn.decode(trans_output[0], skip_special_tokens=True)
 
-    #response = opus_translator(text)
-    return response
-txt=grad.Textbox(lines=1, label="English", placeholder="English Text here")
-out=grad.Textbox(lines=1, label="French")
-grad.Interface(translate, inputs=txt, outputs=out).launch()
 
+def summarize(text):
+    tokens = pegasus_tkn(text, truncation=True, padding="longest", return_tensors="pt")
+    txt_summary = mdl.generate(**tokens)
+    response = pegasus_tkn.batch_decode(txt_summary, 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()