Image-to-3D
Diffusers
Safetensors
LGMFullPipeline
text-to-3d
3d-generation
3d-gaussian-splatting
gaussian-splatting
multi-view-diffusion
lgm
objaverse
research
computer-graphics
Instructions to use WasabiOctopus/LGM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WasabiOctopus/LGM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WasabiOctopus/LGM", 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
Update README.md
Browse files
README.md
CHANGED
|
@@ -210,18 +210,6 @@ This repository is based on the LGM ecosystem and the upstream Hugging Face full
|
|
| 210 |
|
| 211 |
This release is intended as a convenient Hugging Face / Diffusers-compatible resource for research, education, and rapid experimentation.
|
| 212 |
|
| 213 |
-
## 📚 Citation
|
| 214 |
-
|
| 215 |
-
If you use this model or the original LGM method, please cite:
|
| 216 |
-
|
| 217 |
-
```bibtex
|
| 218 |
-
@article{tang2024lgm,
|
| 219 |
-
title={LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation},
|
| 220 |
-
author={Tang, Jiaxiang and Chen, Zhaoxi and Chen, Xiaokang and Wang, Tengfei and Zeng, Gang and Liu, Ziwei},
|
| 221 |
-
journal={arXiv preprint arXiv:2402.05054},
|
| 222 |
-
year={2024}
|
| 223 |
-
}
|
| 224 |
-
```
|
| 225 |
|
| 226 |
<div align="center">
|
| 227 |
|
|
|
|
| 210 |
|
| 211 |
This release is intended as a convenient Hugging Face / Diffusers-compatible resource for research, education, and rapid experimentation.
|
| 212 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 213 |
|
| 214 |
<div align="center">
|
| 215 |
|