Update app.py

app.py

@@ -3,7 +3,9 @@ import torch
 from diffusers import I2VGenXLPipeline
 from diffusers.utils import export_to_gif, load_image
 import tempfile
+import spaces
 
+@spaces.GPU
 def initialize_pipeline():
     # Initialize the pipeline without CUDA support
     pipeline = I2VGenXLPipeline.from_pretrained("ali-vilab/i2vgen-xl", torch_dtype=torch.float16, variant="fp16")
@@ -69,21 +71,4 @@ with gr.Blocks() as demo:
             with gr.Row():
                 with gr.Column():
                     image_prompt = gr.Textbox(lines=2, placeholder="Enter your prompt here...", label="Prompt")
-                    image_input = gr.Image(type="filepath", label="Input Image")
-                    image_negative_prompt = gr.Textbox(lines=2, placeholder="Enter your negative prompt here...", label="Negative Prompt")
-                    image_num_inference_steps = gr.Slider(1, 100, step=1, value=50, label="Number of Inference Steps")
-                    image_guidance_scale = gr.Slider(1, 20, step=0.1, value=9.0, label="Guidance Scale")
-                    image_seed = gr.Number(label="Seed", value=8888)
-                    image_generate_button = gr.Button("Generate GIF")
-
-                with gr.Column():
-                    image_output_video = gr.Video(label="Generated GIF")
-
-            image_generate_button.click(
-                fn=generate_gif,
-                inputs=[image_prompt, image_input, image_negative_prompt, image_num_inference_steps, image_guidance_scale, image_seed],
-                outputs=image_output_video
-            )
-
-# Launch the interface
-demo.launch()
+                    image_input = gr.Image(type="filepath"