Instructions to use alexyan123/NeoVerse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use alexyan123/NeoVerse with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("alexyan123/NeoVerse", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
datasets:
- SpatialVID/SpatialVID
base_model:
- Wan-AI/Wan2.1-T2V-14B
- lightx2v/Wan2.1-T2V-14B-StepDistill-CfgDistill-Lightx2v
pipeline_tag: video-to-video
tags:
- video generation
- 4D World Model
- novel view synthesis
NeoVerse : Enhancing 4D World Model with in-the-wild Monocular Videos
📑 arXiv | 🌐 Project | 🖥️ GitHub | 🤗 Hugging Face | 🤖 ModelScope | 🎞️ BiliBili | 🎥 YouTube
NeoVerse is a versatile 4D world model that is capable of 4D reconstruction, novel-trajectory video generation, and rich downstream applications.
Please refer to the GitHub repository for detailed instructions on how to use the model.
If you find this work helpful, please help star the repository and consider citing it as follows. It would be greatly appreciated!
@article{yang2026neoverse,
author = {Yang, Yuxue and Fan, Lue and Shi, Ziqi and Peng, Junran and Wang, Feng and Zhang, Zhaoxiang},
title = {NeoVerse: Enhancing 4D World Model with in-the-wild Monocular Videos},
journal = {arXiv preprint arXiv:2601.00393},
year = {2026},
}