Update app.py

app.py

@@ -1,5 +1,6 @@
 from transformers import (
     AutoModelForSequenceClassification,  # For text emotion detection model
+    AutoTokenizer,
     pipeline,                           # For creating inference pipeline
     PreTrainedTokenizerFast            # For processing text input
 )
@@ -16,7 +17,7 @@ text_dataDict = {"Time": [], "Emotion": [], "Confidence Score": []}
 face_dataDict = {"Time": [], "Emotion": [], "Confidence Score": []}
 
 emotionDetectModel = AutoModelForSequenceClassification.from_pretrained("borisn70/bert-43-multilabel-emotion-detection") #to be replaced with my fine-tuned model once it is ready
-tokenizer = PreTrainedTokenizerFast(tokenizer_file="tokenizer.json")
+tokenizer = AutoTokenizer.from_pretrained("borisn70/bert-43-multilabel-emotion-detection") #ensure we get correct tokenizer that is compatible with this model by loading it directly from this model
 pipe = pipeline(task="text-classification", model=emotionDetectModel, tokenizer=tokenizer)
 
 localFormat = "%Y-%m-%d %H:%M:%S" #this is how will print the timestamp: year-month-day hour-minutes-seconds (army time)