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from diffusers import DiffusionPipeline
import gradio as gr
import torch
pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v2_576w", torch_dtype=torch.float16)
pipe.to("cuda")
def generate(prompt):
video_frames = pipe(prompt, num_inference_steps=25).frames
return video_frames[0] # return first frame or full video logic
gr.Interface(fn=generate, inputs="text", outputs="image").launch()
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