space updated

app.py

@@ -7,7 +7,7 @@ TOKENIZER = T5Tokenizer.from_pretrained('werent4/mt5TranslatorLT')
 MODEL = MT5ForConditionalGeneration.from_pretrained("werent4/mt5TranslatorLT")
 MODEL.to(DEVICE)
 
-def translate(text, model,device, translation_way = "en-lt"):
+def translate(text, device,translation_way = "en-lt"):
     translations_ways = {
         "en-lt": "<EN2LT>",
         "lt-en": "<LT2EN>"
@@ -17,7 +17,7 @@ def translate(text, model,device, translation_way = "en-lt"):
     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():
-        output_tokens = model.generate(
+        output_tokens = MODEL.generate(
           **encoded_input,
           max_length=128,
           num_beams=5,