Update app.py

app.py

@@ -11,32 +11,21 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 
 hf_token = os.getenv("HF_TOKEN")
 
-aspect_tokenizer = AutoTokenizer.from_pretrained(
-    "EfektMotyla/bert-aspect-ner", token=hf_token
-)
-aspect_model = AutoModelForTokenClassification.from_pretrained(
-    "EfektMotyla/bert-aspect-ner", token=hf_token
-).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", token=hf_token
-)
-sentiment_model = AutoModelForSequenceClassification.from_pretrained(
-    "EfektMotyla/absa-roberta", token=hf_token
-).to(device)
+sentiment_tokenizer = AutoTokenizer.from_pretrained("EfektMotyla/absa-roberta")
+sentiment_model = AutoModelForSequenceClassification.from_pretrained("EfektMotyla/absa-roberta").to(device)
 
 pl_to_en = pipeline(
     "translation",
     model="Helsinki-NLP/opus-mt-pl-en",
-    device=0 if device == "cuda" else -1,
-    token=hf_token
+    device=0 if device == "cuda" else -1
 )
-
 en_to_pl = pipeline(
     "translation",
     model="gsarti/opus-mt-tc-en-pl",
-    device=0 if device == "cuda" else -1,
-    token=hf_token
+    device=0 if device == "cuda" else -1
 )
 
 # === Dane wejściowe i wyjściowe ===