Instructions to use SnowflakeWang/MV-PBRMat-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SnowflakeWang/MV-PBRMat-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("SnowflakeWang/MV-PBRMat-Diffusion", 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
Rename diffusion_pytorch_model.safetensors to controlnet/diffusion_pytorch_model.safetensors
1bba0fd verified - Xet hash:
- e592b8148ffe3bff5481246a777f49ff2cfe90b49ea9721a290f7ac3329a398b
- Size of remote file:
- 1.47 GB
- SHA256:
- db1264f7108066705846b8e7fbc5aed2b685e4ab67c81e843743ee21f1b64667
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