Update app.py

app.py

@@ -25,10 +25,10 @@ def translate_text(input_text, sselected_language, tselected_language, model_nam
                 return f"Error finding model: {model_name_full}! Try other available language combination.", error
     elif model_name.startswith('facebook/nllb'):
         from languagecodes import nllb_language_codes
-        tokenizer = AutoTokenizer.from_pretrained(model_name)
-        model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+        tokenizer = AutoTokenizer.from_pretrained(model_name, token=True, src_lang=nllb_language_codes[sselected_language])
+        model = AutoModelForSeq2SeqLM.from_pretrained(model_name, token=True)
         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=512)
+        translated_text = translator(input_text, max_length=360)
         return translated_text[0]['translation_text'], message_text
     else:
         tokenizer = T5Tokenizer.from_pretrained(model_name)
@@ -40,7 +40,7 @@ def translate_text(input_text, sselected_language, tselected_language, model_nam
         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=512)
+    output_ids = model.generate(input_ids, max_length=360)
     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')