Instructions to use biali/texture-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use biali/texture-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("biali/texture-diffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "pbr brick wall" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download unet/diffusion_pytorch_model.bin from biali/texture-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 3.46 GB
-
https://huggingface.co/biali/texture-diffusion/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://biali/texture-diffusion/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/biali/texture-diffusion/resolve/main/unet/diffusion_pytorch_model.bin
3.46 GB
- Xet hash:
- e998d18e3701e299b85a0a5ca066e145793b895c4053a97aad9260bf36c44d2f
- Size of remote file:
- 3.46 GB
- SHA256:
- fc7f792782b0d7e196befd73e83970d6f27ed9a1a155670d9f8a164b539b05a9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.