Instructions to use uwcc/CowBoy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use uwcc/CowBoy with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("uwcc/CowBoy") prompt = "A church in a field on a sunny day, [trigger] style." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- e7bd3d0670c958d7f4564bee105e9e00b716a147bb6ac06c9c624f70a9aa35d1
- Size of remote file:
- 135 kB
- SHA256:
- d9893aa2bbd44576fe0cb8ac76412cd6378279f2d8060d3fbab55210e2240d6e
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