Update app.py

app.py

@@ -1,6 +1,6 @@
 # Turkish NER Demo for Various Models
 
-from transformers import pipeline, AutoModelForTokenClassification, AutoTokenizer
+from transformers import pipeline, AutoModelForTokenClassification, AutoTokenizer, DebertaV2Tokenizer, DebertaV2Model
 import streamlit as st
 import pandas as pd
 import spacy
@@ -58,8 +58,12 @@ elif input_method == "Write or Paste New Text":
 
 @st.cache(allow_output_mutation=True)
 def setModel(model_checkpoint, aggregation):
-    model = AutoModelForTokenClassification.from_pretrained(model_checkpoint)
-    tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
+    if model_checkpoint == "akdeniz27/mDeBERTa-v3-base-turkish-ner":
+        model = DebertaV2Model.from_pretrained(model_checkpoint)
+        tokenizer = DebertaV2Tokenizer.from_pretrained(model_checkpoint)
+    else:
+        model = AutoModelForTokenClassification.from_pretrained(model_checkpoint)
+        tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
     return pipeline('ner', model=model, tokenizer=tokenizer, aggregation_strategy=aggregation)
 
 @st.cache(allow_output_mutation=True)