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 text_encoder/pytorch_model.bin from biali/texture-diffusion: direct link, hf CLI and curl.
- Browser
- Download file 1.36 GB
-
https://huggingface.co/biali/texture-diffusion/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://biali/texture-diffusion/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/biali/texture-diffusion/resolve/main/text_encoder/pytorch_model.bin
1.36 GB
- Xet hash:
- 08524a12c7a0272bb8f51f0ad6ebf2e9524a92ac44391f90e309a939c5f4f49c
- Size of remote file:
- 1.36 GB
- SHA256:
- 79f0837852c1f791440c3cf6fab4e734f9169028dd9545bd46b9cd39962bbb07
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