k

app.py

@@ -1,10 +1,10 @@
 import gradio as gr
 from transformers import pipeline
 
-captioner = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning")
+pipe = pipeline("image-to-text", model="nlpconnect/vit-gpt2-image-captioning")
 
 def generate_caption(image):
-    result = captioner(image)
+    result = pipe(image)
     return result[0]["generated_text"].strip()
 
 title = "🖼️ Image Caption Generator"
@@ -16,7 +16,7 @@ demo = gr.Interface(
     outputs=gr.Textbox(label="Generated Caption"),
     title=title,
     description=description,
-    allow_flagging="never"
+    flagging_mode="never"
 )
 
 if __name__ == "__main__":