Update app.py

app.py

@@ -3,24 +3,25 @@ import gradio as gr
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, AutoModelForTokenClassification
 import os
 
+auth_token = os.environ['HF_TOKEN']
+
 # Load the tokenizer and models for the first pipeline
-tokenizer_ext = AutoTokenizer.from_pretrained("AlGe/deberta-v3-large_token")
-model_ext = AutoModelForTokenClassification.from_pretrained("AlGe/deberta-v3-large_token")
+tokenizer_ext = AutoTokenizer.from_pretrained("AlGe/deberta-v3-large_token", token=auth_token)
+model_ext = AutoModelForTokenClassification.from_pretrained("AlGe/deberta-v3-large_token", token=auth_token)
 tokenizer_ext.model_max_length = 512
 pipe_ext = gr.pipeline("ner", model=model_ext, tokenizer=tokenizer_ext)
 
 # Load the tokenizer and models for the second pipeline
-tokenizer_ais = AutoTokenizer.from_pretrained("AlGe/deberta-v3-large_AIS-token")
-model_ais = AutoModelForTokenClassification.from_pretrained("AlGe/deberta-v3-large_AIS-token")
+tokenizer_ais = AutoTokenizer.from_pretrained("AlGe/deberta-v3-large_AIS-token", token=auth_token)
+model_ais = AutoModelForTokenClassification.from_pretrained("AlGe/deberta-v3-large_AIS-token", token=auth_token)
 tokenizer_ais.model_max_length = 512
 pipe_ais = gr.pipeline("ner", model=model_ais, tokenizer=tokenizer_ais)
 
 # Load the tokenizer and models for the third pipeline
-auth_token = os.environ['HF_TOKEN']
-model1 = AutoModelForSequenceClassification.from_pretrained("AlGe/deberta-v3-large_Int_segment", num_labels=1, use_auth_token=auth_token)
-tokenizer1 = AutoTokenizer.from_pretrained("AlGe/deberta-v3-large_Int_segment", use_auth_token=auth_token)
+model1 = AutoModelForSequenceClassification.from_pretrained("AlGe/deberta-v3-large_Int_segment", num_labels=1, token=auth_token)
+tokenizer1 = AutoTokenizer.from_pretrained("AlGe/deberta-v3-large_Int_segment", token=auth_token)
 
-model2 = AutoModelForSequenceClassification.from_pretrained("AlGe/deberta-v3-large_seq_ext", num_labels=1, use_auth_token=auth_token)
+model2 = AutoModelForSequenceClassification.from_pretrained("AlGe/deberta-v3-large_seq_ext", num_labels=1, token=auth_token)
 
 # Define functions to process inputs
 def process_ner(text, pipeline):