uses anger model

app.py

@@ -9,8 +9,8 @@ def formatOutput(modelOutput):
 
 def processInput(input): 
     #load model and tokenizer
-    model = AutoModelForSequenceClassification.from_pretrained("garrettbaber/twitter-roberta-base-joy-intensity")
-    tokenizer = AutoTokenizer.from_pretrained("garrettbaber/twitter-roberta-base-joy-intensity")
+    model = AutoModelForSequenceClassification.from_pretrained("garrettbaber/twitter-roberta-base-anger-intensity")
+    tokenizer = AutoTokenizer.from_pretrained("garrettbaber/twitter-roberta-base-anger-intensity")
     #get tokens
     tokens = tokenizer(input, return_tensors="pt")
     #pass tokens to model