Instructions to use wgsxm/PartCrafter-Scene with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wgsxm/PartCrafter-Scene with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wgsxm/PartCrafter-Scene", 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": "PartCrafterPipeline", | |
| "_diffusers_version": "0.34.0", | |
| "feature_extractor_dinov2": [ | |
| "transformers", | |
| "BitImageProcessor" | |
| ], | |
| "image_encoder_dinov2": [ | |
| "transformers", | |
| "Dinov2Model" | |
| ], | |
| "scheduler": [ | |
| "src.schedulers.scheduling_rectified_flow", | |
| "RectifiedFlowScheduler" | |
| ], | |
| "transformer": [ | |
| "src.models.transformers.partcrafter_transformer", | |
| "PartCrafterDiTModel" | |
| ], | |
| "vae": [ | |
| "src.models.autoencoders.autoencoder_kl_triposg", | |
| "TripoSGVAEModel" | |
| ] | |
| } | |