run_video.py

#!/usr/bin/env python3
import torch
from diffusers import DiffusionPipeline, DPMSolverMultistepScheduler
from diffusers.utils import export_to_video
from PIL import Image

# Make sure CUDA has < 13GB VRAM
# torch.cuda.set_per_process_memory_fraction(0.5)

pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v2_576w", torch_dtype=torch.float16)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
# pipe.enable_model_cpu_offload()
pipe.to("cuda")
pipe.enable_vae_slicing()

pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)

prompt = "Darth Vader is surfing on waves"
video_frames = pipe(prompt, num_inference_steps=40, height=320, width=576, num_frames=36).frames
video_path = export_to_video(video_frames, output_video_path="/home/patrick/videos/video_576_darth_vader_36.mp4")

pipe = DiffusionPipeline.from_pretrained("cerspense/zeroscope_v2_XL", torch_dtype=torch.float16)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
pipe.enable_model_cpu_offload()
pipe.enable_vae_slicing()

video = [Image.fromarray(frame).resize((1024, 576)) for frame in video_frames]

video_frames = pipe(prompt, video=video, strength=0.6).frames
video_path = export_to_video(video_frames, output_video_path="/home/patrick/videos/video_1024_darth_vader_36.mp4")