Instructions to use falgasdev/z-brushwork with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use falgasdev/z-brushwork with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Tongyi-MAI/Z-Image-Turbo", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("falgasdev/z-brushwork") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download images/zbrush.webp from falgasdev/z-brushwork: direct link, hf CLI and curl.
- Browser
- Download file 12.3 kB
-
https://huggingface.co/falgasdev/z-brushwork/resolve/main/images/zbrush.webp
- Command line
-
hf download hf://falgasdev/z-brushwork/images/zbrush.webp
-
curl -L -o zbrush.webp https://huggingface.co/falgasdev/z-brushwork/resolve/main/images/zbrush.webp
12.3 kB

- Xet hash:
- b8cdaedf1f7f1743ce8caa6eb98043c001debb3351d3b082b5712a76e1ff5054
- Size of remote file:
- 12.3 kB
- SHA256:
- 3471575b79c029e23e0bca7431fcbd0b5b82571ee5172b4690bcc4b37fd441b5
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