Update app.py

app.py

@@ -7,8 +7,8 @@ torch.cuda.is_available()
 
 model_path = "ltg/norbert3-base_sentence-sentiment"
 
-tokenizer = AutoTokenizer.from_pretrained(model_path)
-config = AutoConfig.from_pretrained(model_path)
+tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
+config = AutoConfig.from_pretrained(model_path, trust_remote_code=True)
 model = AutoModelForSequenceClassification.from_pretrained(model_path, trust_remote_code=True)
 
 def sentiment_analysis(text):
@@ -16,7 +16,7 @@ def sentiment_analysis(text):
     output = model(**encoded_input)
     scores_ = output[0][0].detach().numpy()
     scores_ = softmax(scores_)
-    labels = ['Negativ', 'Nøytral', 'Positiv']
+    labels = ['Negativ', 'Positiv', 'Nøytral']
     scores = {l: float(s) for (l, s) in zip(labels, scores_)}
     return scores