chatgpt

app.py

@@ -1,20 +1,11 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
-from transformers import AutoModelForSeq2SeqLM
-from transformers import AutoTokenizer
+# 모델과 토크나이저는 한 번만 로드되도록 함수 외부에 선언
+model = AutoModelForSeq2SeqLM.from_pretrained("Kyudan/opus-mt-en-ro-finetuned-en-to-ro")
+tokenizer = AutoTokenizer.from_pretrained("Kyudan/opus-mt-en-ro-finetuned-en-to-ro")
 
 def respond(text):
-    model = AutoModelForSeq2SeqLM.from_pretrained("Kyudan/opus-mt-en-ro-finetuned-en-to-ro")
-    model.eval()
-    
-
-    # 토크나이저 로드
-    tokenizer = AutoTokenizer.from_pretrained("Kyudan/opus-mt-en-ro-finetuned-en-to-ro")
-
-    # 번역할 입력 텍스트
-    text = text
-
     # 입력 텍스트를 토큰화
     inputs = tokenizer.encode(text, return_tensors="pt")
 
@@ -25,14 +16,14 @@ def respond(text):
     translated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
     return translated_text
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    title = "translate English to Romanian"
-)
 
+# Gradio 인터페이스 설정
+demo = gr.Interface(
+    fn=respond,
+    inputs="text",
+    outputs="text",
+    title="Translate English to Romanian"
+)
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(share=True)