Create app.py

app.py

@@ -1,21 +1,7 @@
-from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
-import streamlit as st
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-# Hugging Face 모델 로드
-tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")  # 모델 이름 변경
-model = TFAutoModelForSequenceClassification.from_pretrained("bert-base-uncased")
+# 로컬 경로 지정
+model_path = "Download"
 
-# Streamlit 앱
-st.title("Text Analysis with Hugging Face Model")
-st.write("Enter text below to analyze it using the selected Hugging Face model.")
-
-# 입력 필드
-input_text = st.text_input("Enter text here:")
-if st.button("Analyze"):
-    try:
-        inputs = tokenizer(input_text, return_tensors="tf")
-        outputs = model(**inputs)
-        logits = outputs.logits.numpy().tolist()
-        st.write("Model Output (logits):", logits)
-    except Exception as e:
-        st.error(f"Error during model inference: {e}")
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_path)