Update app.py

app.py

@@ -29,7 +29,7 @@ def translate_text(input_text, sselected_language, tselected_language, model_nam
         tokenizer = AutoTokenizer.from_pretrained(model_name, src_lang=nllb_language_codes[sselected_language])
         model = AutoModelForSeq2SeqLM.from_pretrained(model_name, device_map="auto")
         translator = pipeline('translation', model=model, tokenizer=tokenizer, src_lang=nllb_language_codes[sselected_language], tgt_lang=nllb_language_codes[tselected_language])
-        translated_text = translator(input_text, max_length=360)
+        translated_text = translator(input_text, max_length=512)
         return translated_text[0]['translation_text'], message_text
     else:
         tokenizer = T5Tokenizer.from_pretrained(model_name)
@@ -39,13 +39,15 @@ def translate_text(input_text, sselected_language, tselected_language, model_nam
     if torch.cuda.is_available():
         model = model.to('cuda')
         print("CUDA is available! Using GPU.")
+    else:
+        print("CUDA not available! Using CPU.")
     if model_name.startswith("Helsinki-NLP"):
         prompt = input_text
     else:
         prompt = f"translate {sselected_language} to {tselected_language}: {input_text}"
 
     input_ids = tokenizer.encode(prompt, return_tensors="pt")
-    output_ids = model.generate(input_ids, max_length=360)
+    output_ids = model.generate(input_ids, max_length=512)
     translated_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
     
     print(f'Translating from {sselected_language} to {tselected_language} with {model_name}:', f'{input_text} =  {translated_text}', sep='\n')