Update app.py

app.py

@@ -1,11 +1,14 @@
 import streamlit as st
 from transformers import AutoTokenizer, AutoModelForTokenClassification
 from transformers import pipeline
+import os
+
+# Define the path where model and tokenizer files are located
+model_directory = "AdilHayat173/token_classification"
 
 # Load the model and tokenizer
-model_name = "AdilHayat173/token_classifcation"  
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForTokenClassification.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_directory)
+model = AutoModelForTokenClassification.from_pretrained(model_directory)
 nlp = pipeline("ner", model=model, tokenizer=tokenizer, aggregation_strategy="simple")
 
 st.title("Token Classification with Hugging Face")
@@ -17,7 +20,7 @@ if st.button("Classify Text"):
     if user_input:
         # Token classification
         results = nlp(user_input)
-        
+
         # Display results
         st.write("### Token Classification Results")
         for entity in results: