import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("zzsi/DOVE", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
DOVE Model Checkpoints
This repository hosts model checkpoints for DOVE (Diffusion Priors for Video Super-Resolution).
This is not my work. All credit goes to the original authors. Please refer to the official repository for the paper, code, and license.
Contents
stage2/— Stage 2 model checkpoint (diffusion transformer, text encoder, VAE, tokenizer, scheduler)
Citation
Please cite the original paper if you use these checkpoints:
@inproceedings{zheng2025dove,
title={DOVE: Diffusion Priors for Video Super-Resolution},
author={Zheng, Chen and others},
year={2025}
}
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