Update app.py

app.py

@@ -1,18 +1,18 @@
-    
 
 import gradio as gr
 from transformers import pipeline, AutoModelForQuestionAnswering, AutoTokenizer, AutoModelForTokenClassification
 
 # Load your custom model and tokenizer
 qa_model_name = "erdometo/xlm-roberta-base-finetuned-TQuad2"
-token_classification_model_name = "FacebookAI/xlm-roberta-large-finetuned-conll03-german"
+token_classification_model_name = "akdeniz27/convbert-base-turkish-cased-ner"
 
 qa_model = AutoModelForQuestionAnswering.from_pretrained(qa_model_name)
 qa_tokenizer = AutoTokenizer.from_pretrained(qa_model_name)
 
 token_classification_model = AutoModelForTokenClassification.from_pretrained(token_classification_model_name)
 token_classification_tokenizer = AutoTokenizer.from_pretrained(token_classification_model_name)
-# Define a function for inference based on pipeline type
+
+
 def predict(pipeline_type, question, context):
     if pipeline_type == "question-answering":
         qa_pipeline = pipeline("question-answering", model=qa_model, tokenizer=qa_tokenizer)