Update app.py

app.py

@@ -2,31 +2,6 @@ import gradio as gr
 import torch
 from transformers import BlipForQuestionAnswering, AutoProcessor
 from PIL import Image
-import spaces
-
-# Check device
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-
-# Load model and processor
-model = BlipForQuestionAnswering.from_pretrained("Salesforce/blip-vqa-base").to(device)
-processor = AutoProcessor.from_pretrained("Salesforce/blip-vqa-base")
-
-@spaces.GPU  # ZeroGPU: Allocate GPU only when generating images
-def answer_question(image, question):
-    inputs = processor(image, question, return_tensors="pt").to(device)
-    out = model.generate(**inputs)
-    return processor.decode(out[0], skip_special_tokens=True)
-
-iface = gr.Interface(
-    fn=answer_question,
-    inputs=[gr.Image(type="pil"), gr.Textbox(placeholder="Enter your question")],
-    outputs=gr.Textbox(label="Answer"),
-    title="Visual Question Answering with BLIP",
-    description="Upload an image and ask a question about its content.",
-import gradio as gr
-import torch
-from transformers import BlipForQuestionAnswering, AutoProcessor
-from PIL import Image
 
 # Check device
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -50,5 +25,3 @@ iface = gr.Interface(
 )
 
 iface.launch()
-
-