Faster default configs

app.py

@@ -20,7 +20,6 @@ import os
 import gradio as gr
 import numpy as np
 import PIL.Image
-import spaces
 import torch
 
 from diffnext.pipelines import NOVAPipeline
@@ -56,7 +55,6 @@ def crop_image(image, target_h, target_w):
     return np.array(image.resize((target_w, target_h), PIL.Image.Resampling.BILINEAR))
 
 
-@spaces.GPU(duration=180)
 def generate_video(
     prompt,
     negative_prompt,
@@ -139,13 +137,13 @@ if __name__ == "__main__":
     )
     image_prompt = gr.Image(label="Image Prompt (Optional) ", type="pil")
     # fmt: off
-    adv_opt = gr.Accordion("Advanced Options", open=False).__enter__()
+    adv_opt = gr.Accordion("Advanced Options", open=True).__enter__()
     seed = gr.Slider(label="Seed", maximum=2147483647, step=1, value=0)
     randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
     guidance_scale = gr.Slider(label="Guidance scale", minimum=1, maximum=10.0, step=0.1, value=7.0)
     with gr.Row():
-        num_inference_steps = gr.Slider(label="Inference steps", minimum=1, maximum=128, step=1, value=128)  # noqa
-        num_diffusion_steps = gr.Slider(label="Diffusion steps", minimum=1, maximum=100, step=1, value=100)  # noqa
+        num_inference_steps = gr.Slider(label="Inference steps", minimum=1, maximum=128, step=1, value=64)  # noqa
+        num_diffusion_steps = gr.Slider(label="Diffusion steps", minimum=1, maximum=100, step=1, value=50)  # noqa
     adv_opt.__exit__()
     generate = gr.Button("Generate Video", variant="primary", size="lg")
     input_col.__exit__()