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
Download unet/diffusion_pytorch_model.bin from SnowflakeWang/MV-PBRMat-Diffusion: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/SnowflakeWang/MV-PBRMat-Diffusion/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://SnowflakeWang/MV-PBRMat-Diffusion/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/SnowflakeWang/MV-PBRMat-Diffusion/resolve/main/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- 6c30b3c571c6e3977ae0c39ed64b53122ac075d4dd349fa18344d99555e9045a
- Size of remote file:
- 3.46 GB
- SHA256:
- 6ebf3f369f49abc6708acdc2c7247d1c8d5a0c58628e33481f48684133db18f2
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