Instructions to use Yanrui95/NormalCrafter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yanrui95/NormalCrafter with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yanrui95/NormalCrafter", 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": "AutoencoderKLTemporalDecoder", | |
| "_diffusers_version": "0.31.0", | |
| "_name_or_path": "outputs/normal_vae/hypersim_marigold_split_768x576_fixSeed/checkpoint-20000/unet/", | |
| "block_out_channels": [ | |
| 128, | |
| 256, | |
| 512, | |
| 512 | |
| ], | |
| "down_block_types": [ | |
| "DownEncoderBlock2D", | |
| "DownEncoderBlock2D", | |
| "DownEncoderBlock2D", | |
| "DownEncoderBlock2D" | |
| ], | |
| "force_upcast": true, | |
| "in_channels": 3, | |
| "latent_channels": 4, | |
| "layers_per_block": 2, | |
| "out_channels": 3, | |
| "sample_size": 768, | |
| "scaling_factor": 0.18215 | |
| } | |