updated app with my model

app.py

@@ -1,27 +1,24 @@
 import gradio as gr
-from transformers import BlipProcessor, BlipForConditionalGeneration
 from PIL import Image
 import torch
+from transformers import BlipProcessor, BlipForConditionalGeneration
 
-# Example with BLIP (replace with your fine-tuned model)
 processor = BlipProcessor.from_pretrained("zeddotes/blip-computer-thoughts")
 model = BlipForConditionalGeneration.from_pretrained("zeddotes/blip-computer-thoughts")
 
 def caption_image(image):
-    if image is None:
-        return "No image provided"
     inputs = processor(images=image, return_tensors="pt")
     with torch.no_grad():
-        out = model.generate(**inputs)
-    caption = processor.decode(out[0], skip_special_tokens=True)
+        generated_ids = model.generate(**inputs)
+    caption = processor.decode(generated_ids[0], skip_special_tokens=True)
     return caption
 
 demo = gr.Interface(
     fn=caption_image,
     inputs=gr.Image(type="pil"),
     outputs="text",
-    title="Custom UI Action Description"
+    title="My Fine-Tuned Model"
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()