Update app.py

app.py

@@ -1,21 +1,24 @@
 import gradio as gr
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 import torch
+import spaces  # Import spaces for ZeroGPU compatibility
 
 # Load the models and tokenizers for each translation direction
 # Faroese to English
 model_faero_eng = AutoModelForSeq2SeqLM.from_pretrained("barbaroo/nllb_200_600M_fo_en")
-tokenizer_faero_eng = AutoTokenizer.from_pretrained("barbaroo/nllb_200_600M_fo_en", src_lang ="fao_Latn" )
+tokenizer_faero_eng = AutoTokenizer.from_pretrained("barbaroo/nllb_200_600M_fo_en", src_lang="fao_Latn")
 
 # English to Faroese
 model_eng_faero = AutoModelForSeq2SeqLM.from_pretrained("barbaroo/nllb_200_1.3B_en_fo")
-tokenizer_eng_faero = AutoTokenizer.from_pretrained("barbaroo/nllb_200_1.3B_en_fo", src_lang ="eng_Latn")
+tokenizer_eng_faero = AutoTokenizer.from_pretrained("barbaroo/nllb_200_1.3B_en_fo", src_lang="eng_Latn")
 
 # Check if GPU is available
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 model_faero_eng.to(device)
 model_eng_faero.to(device)
 
+# Use @spaces.GPU to specify GPU usage for the translation function
+@spaces.GPU  # Apply ZeroGPU decorator
 def translate(text, direction):
     if direction == "Faroese to English":
         # Encode the text for Faroese to English