space updated

app.py

@@ -7,13 +7,13 @@ TOKENIZER = T5Tokenizer.from_pretrained('werent4/mt5TranslatorLT')
 MODEL = MT5ForConditionalGeneration.from_pretrained("werent4/mt5TranslatorLT")
 MODEL.to(DEVICE)
 
-def translate(text, max_length, num_beams, translation_way = "en-lt"):
+def translate(text, max_length, num_beams, translation_way):
     translations_ways = {
         "en-lt": "<EN2LT>",
         "lt-en": "<LT2EN>"
     }
     if translation_way not in translations_ways:
-        raise ValueError(f"Invalid translation way. Supported ways: {list(translations_ways.keys())}")
+        raise ValueError(f"Invalid translation way: {translation_way}. Supported ways: {list(translations_ways.keys())}")
     input_text = f"{translations_ways[translation_way]} {text}"
     encoded_input = TOKENIZER(input_text, return_tensors="pt", padding=True, truncation=True, max_length=128).to(DEVICE)
     with torch.no_grad():