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", torch_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
- Xet hash:
- 9f3c5afa96a83f5f8ff1db01f0bfef2ec2c11978a225956eefeb75964e49e75b
- Size of remote file:
- 102 MB
- SHA256:
- 545ac34a84687aab0f545ae211b91224a7e8dffe7c7b4593ebcf5a83631d0a9a
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