Update app.py

app.py

@@ -8,26 +8,11 @@ model = PegasusForConditionalGeneration.from_pretrained(model_name)
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 model = model.to(device)
 
-def translate_to_english(model, tokenizer, text):
-  translated_text = []
-  text = "paraphrase: " + text + " </s>"
-  encoding = tokenizer.encode_plus(text,pad_to_max_length=True, return_tensors="pt")
-  input_ids, attention_masks = encoding["input_ids"].to(device), encoding["attention_mask"].to(device)
-  beam_outputs = model.generate(
-    input_ids=input_ids, attention_mask=attention_masks,
-    do_sample=True,
-    max_length=256,
-    top_k=120,
-    temperature=1.5,
-    top_p=0.98,
-    early_stopping=True,
-    num_return_sequences=10
-  )
-  for beam_output in beam_outputs:
-    sent = tokenizer.decode(beam_output, skip_special_tokens=True,clean_up_tokenization_spaces=True)
-    print(sent)
-    translated_text.append(sent)
-  return translated_text
+def get_response(text):
+  batch = tokenizer([input_text],truncation=True,padding='longest',max_length=60, return_tensors="pt").to(device)
+  translated = model.generate(**batch,max_length=60, do_sample=True, num_return_sequences=10, temperature=1.5)
+  tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)
+  return tgt_text
     
 st.title("Auto Translate (To English)")
 text = st.text_input("Okay")
@@ -35,5 +20,5 @@ st.text("What you wrote: ")
 st.write(text)
 st.text("English Translation: ")
 if text:
-    translated_text = translate_to_english(model, tokenizer, text)
+    translated_text = translate_to_english(text)
     st.write(translated_text if translated_text else "No translation found")