Update app.py

app.py

@@ -3,23 +3,18 @@ import torch
 from diffusers import I2VGenXLPipeline
 from diffusers.utils import export_to_gif, load_image
 import tempfile
-import spaces
 
-@spaces.GPU
-def initialize_pipeline(device):
-    # Initialize the pipeline with CUDA support
+def initialize_pipeline():
+    # Initialize the pipeline without CUDA support
     pipeline = I2VGenXLPipeline.from_pretrained("ali-vilab/i2vgen-xl", torch_dtype=torch.float16, variant="fp16")
-    pipeline.to(device)
     return pipeline
 
 def generate_gif(prompt, image, negative_prompt, num_inference_steps, guidance_scale, seed):
-    # Check if CUDA is available and set the device
-
     # Initialize the pipeline within the function
-    pipeline = initialize_pipeline(device)
+    pipeline = initialize_pipeline()
 
     # Set the generator seed
-    generator = torch.Generator(device=device).manual_seed(seed)
+    generator = torch.Generator().manual_seed(seed)
 
     # Check if an image is provided
     if image is not None:
@@ -66,7 +61,7 @@ with gr.Blocks() as demo:
 
             text_generate_button.click(
                 fn=generate_gif,
-                inputs=[text_prompt, gr.Image(type="filepath", label="Input Image (optional)", visible=False), text_negative_prompt, text_num_inference_steps, text_guidance_scale, text_seed],
+                inputs=[text_prompt, None, text_negative_prompt, text_num_inference_steps, text_guidance_scale, text_seed],
                 outputs=text_output_video
             )