Update app.py

app.py

@@ -1,4 +1,4 @@
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
+from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
 import streamlit as st
 import os
 import tensorflow as tf
@@ -6,11 +6,10 @@ from absl import logging
 
 # Hugging Face 모델 설정
 tokenizer = AutoTokenizer.from_pretrained("snunlp/KR-FinBert-SC")
-model = AutoModelForSequenceClassification.from_pretrained("snunlp/KR-FinBert-SC")
+model = TFAutoModelForSequenceClassification.from_pretrained("snunlp/KR-FinBert-SC")
 
 # 환경 변수 설정
 os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'  # oneDNN 최적화 비활성화
-os.environ["CUDA_VISIBLE_DEVICES"] = "-1"  # GPU 비활성화 (필요 시)
 
 # 로그 초기화
 logging.set_verbosity(logging.INFO)
@@ -28,8 +27,8 @@ st.write("This is a sample Streamlit app.")
 input_text = st.text_input("Enter some text:")
 if st.button("Analyze"):
     try:
-        inputs = tokenizer(input_text, return_tensors="pt")
+        inputs = tokenizer(input_text, return_tensors="tf")  # TensorFlow의 경우 'tf'를 명시
         outputs = model(**inputs)
-        st.write("Model Output:", outputs.logits.tolist())
+        st.write("Model Output:", outputs.logits.numpy().tolist())
     except Exception as e:
         st.error(f"Error during model inference: {e}")