Update app.py

app.py

@@ -3,10 +3,10 @@ import torch
 from huggingface_hub import hf_hub_download
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
 
-translator_nllb = pipeline("translation", model="facebook/nllb-200-distilled-600M") 
-# translator_marion_en = pipeline("translation", model="mbarnig/MarianNMT-tatoeba-en-lb")
-translator_marion_lb = pipeline("translation", model="mbarnig/MarianNMT-tatoeba-lb-en")
-translate_t5_mt5 = pipeline("translation", model="mbarnig/T5-mt5-tatoeba-en-lb")
+model_checkpoint_nllb = "facebook/nllb-200-distilled-600M" 
+model_checkpoint_marion_en = "mbarnig/MarianNMT-tatoeba-en-lb"
+model_checkpoint_marion_lb = "mbarnig/MarianNMT-tatoeba-lb-en"
+model_checkpoint_t5_mt5 = "mbarnig/T5-mt5-tatoeba-en-lb"
 
 my_title = "🇬🇧 Mir iwwersetzen vun an op Lëtzebuergesch ! 🇫🇷"
 my_description = "English-Luxembourgish machine translation (MT) demo based on 3 open-source transformer models: Facebook-NLLB, Microsoft-MarianNMT & Google-T5/mt5."
@@ -36,7 +36,8 @@ my_output = gr.Textbox(lines=5, label="Translation")
 
 def iwwersetz(source_text, model, direc):
     if model == "NLLB":
-        if direc == "en -> lb":
+        translator = pipeline("translation", model=model_checkpoint) 
+        if direc == "en -> lb":         
             # translation = translator("en", "lb", source_text)
             translation = source_text
         else: