Update app.py

app.py

@@ -9,18 +9,19 @@ import torch
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 # === Tokenizery i modele ABSA ===
-with gr.StatusTracker("Ładowanie modeli..."):
-    aspect_tokenizer = AutoTokenizer.from_pretrained("EfektMotyla/bert-aspect-ner")
-    aspect_model = AutoModelForTokenClassification.from_pretrained("EfektMotyla/bert-aspect-ner").to(device)
+aspect_tokenizer = AutoTokenizer.from_pretrained("EfektMotyla/bert-aspect-ner")
+aspect_model = AutoModelForTokenClassification.from_pretrained("EfektMotyla/bert-aspect-ner").to(device)
 
-    sentiment_tokenizer = AutoTokenizer.from_pretrained("EfektMotyla/absa-roberta")
-    sentiment_model = AutoModelForSequenceClassification.from_pretrained("EfektMotyla/absa-roberta").to(device)
+sentiment_tokenizer = AutoTokenizer.from_pretrained("EfektMotyla/absa-roberta")
+sentiment_model = AutoModelForSequenceClassification.from_pretrained("EfektMotyla/absa-roberta").to(device)
+
+en_to_pl_tokenizer = MarianTokenizer.from_pretrained("gsarti/opus-mt-tc-en-pl")
+en_to_pl_model = MarianMTModel.from_pretrained("gsarti/opus-mt-tc-en-pl").to(device)
+
+pl_to_en_tokenizer = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-pl-en")
+pl_to_en_model = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-pl-en").to(device)
 
-    en_to_pl_tokenizer = MarianTokenizer.from_pretrained("gsarti/opus-mt-tc-en-pl")
-    en_to_pl_model = MarianMTModel.from_pretrained("gsarti/opus-mt-tc-en-pl").to(device)
 
-    pl_to_en_tokenizer = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-pl-en")
-    pl_to_en_model = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-pl-en").to(device)
 
 def translate(texts, tokenizer, model):
     inputs = tokenizer(texts, return_tensors="pt", padding=True, truncation=True).to(device)