Instructions to use suvadityamuk/Step1X-3D-Geometry-1300m-diffusers-3d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use suvadityamuk/Step1X-3D-Geometry-1300m-diffusers-3d with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("suvadityamuk/Step1X-3D-Geometry-1300m-diffusers-3d", 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 vae/config.json from suvadityamuk/Step1X-3D-Geometry-1300m-diffusers-3d: direct link, hf CLI and curl.
- Browser
- Download file 283 Bytes
-
https://huggingface.co/suvadityamuk/Step1X-3D-Geometry-1300m-diffusers-3d/resolve/main/vae/config.json
- Command line
-
hf download hf://suvadityamuk/Step1X-3D-Geometry-1300m-diffusers-3d/vae/config.json
-
curl -L -o config.json https://huggingface.co/suvadityamuk/Step1X-3D-Geometry-1300m-diffusers-3d/resolve/main/vae/config.json
283 Bytes
| { | |
| "_class_name": "Step1X3DShapeDecoder", | |
| "_diffusers_version": "0.41.0.dev0", | |
| "include_pi": false, | |
| "latent_channels": 64, | |
| "num_attention_heads": 12, | |
| "num_freqs": 8, | |
| "num_latents": 2048, | |
| "num_layers": 16, | |
| "out_channels": 1, | |
| "scaling_factor": 1.0, | |
| "width": 768 | |
| } | |