Instructions to use OzzyGT/Pixal3D_Modular with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OzzyGT/Pixal3D_Modular with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OzzyGT/Pixal3D_Modular", 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
Download NOTICE from OzzyGT/Pixal3D_Modular: direct link, hf CLI and curl.
- Browser
- Download file 412 Bytes
-
https://huggingface.co/OzzyGT/Pixal3D_Modular/resolve/main/NOTICE
- Command line
-
hf download hf://OzzyGT/Pixal3D_Modular/NOTICE
-
curl -L -o NOTICE https://huggingface.co/OzzyGT/Pixal3D_Modular/resolve/main/NOTICE
412 Bytes
| The camera projection (projection.py) and the latent normalization statistics (normalization.py) are adapted from: | |
| Pixal3D, Copyright (c) 2026 Tencent, MIT ( LICENSE-PIXAL3D). | |
| https://github.com/TencentARC/Pixal3D | |
| Reference revision: f7cf384 | |
| The remaining block code is original and licensed under Apache-2.0 ( LICENSE). | |
| The package contains no learned weights. Converted checkpoint licensing is separate. | |