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, device,translation_way = "en-lt"):
+def translate(text, device, max_length, num_beams, translation_way = "en-lt"):
     translations_ways = {
         "en-lt": "<EN2LT>",
         "lt-en": "<LT2EN>"
@@ -19,8 +19,8 @@ def translate(text, device,translation_way = "en-lt"):
     with torch.no_grad():
         output_tokens = MODEL.generate(
           **encoded_input,
-          max_length=128,
-          num_beams=5,
+          max_length=max_length,
+          num_beams=num_beams,
           no_repeat_ngram_size=2,
           early_stopping=True
       )