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
File size: 746 Bytes
e1b0960 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | {
"_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"
]
}
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