Instructions to use falgasdev/oiledskin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use falgasdev/oiledskin 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/oiledskin") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Add 2 files
Browse files
OiledSkin_Zit_Turbo_V1.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:571931c3e0c76b01efa41a6353971700d308aec13494de9a6127649d548e4306
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size 170128280
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images/oilyskin.png
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Git LFS Details
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