Instructions to use AndyMOU/Step1X-3D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AndyMOU/Step1X-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("AndyMOU/Step1X-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
| { | |
| "_class_name": "Step1X3DGeometryPipeline", | |
| "_diffusers_version": "0.32.2", | |
| "caption_encoder": [ | |
| null, | |
| null | |
| ], | |
| "label_encoder": [ | |
| "step1x3d_geometry.models.conditional_encoders.label_encoder", | |
| "LabelEncoder" | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "FlowMatchEulerDiscreteScheduler" | |
| ], | |
| "transformer": [ | |
| "step1x3d_geometry.models.transformers.flux_transformer_1d", | |
| "FluxDenoiser" | |
| ], | |
| "vae": [ | |
| "step1x3d_geometry.models.autoencoders.michelangelo_autoencoder", | |
| "MichelangeloAutoencoder" | |
| ], | |
| "visual_eature_extractor": [ | |
| "transformers", | |
| "BitImageProcessor" | |
| ], | |
| "visual_encoder": [ | |
| "step1x3d_geometry.models.conditional_encoders.dinov2_clip_encoder", | |
| "Dinov2CLIPEncoder" | |
| ] | |
| } | |