Try deberta v2 as tokenizer

app.py

@@ -51,7 +51,7 @@ model_name = "CarolXia/pii-kd-deberta-v2"
 model = DebertaV2ForTokenClassification.from_pretrained(model_name, token=st.secrets["HUGGINGFACE_TOKEN"])
 # Try quantization instead
 # model = AutoModelForTokenClassification.from_pretrained(model_name, device_map="auto", load_in_8bit=True)
-tokenizer = DebertaV2Tokenizer.from_pretrained(model_name, token=st.secrets["HUGGINGFACE_TOKEN"])
+tokenizer = DebertaV2Tokenizer.from_pretrained("microsoft/mdeberta-v3-base", token=st.secrets["HUGGINGFACE_TOKEN"])
 recognizer = pipeline("ner", model=model, tokenizer=tokenizer)
 # model_name = "urchade/gliner_multi_pii-v1"
 # model = GLiNER.from_pretrained(model_name)