Instructions to use fagenorn/cuco-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fagenorn/cuco-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("fagenorn/cuco-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f514371bec21b676b204ec5a989b10d3067551c386613fc04a278797ce309b40
- Size of remote file:
- 6.59 MB
- SHA256:
- 8176df2d4409fe1a3e3163d14a5111b98b2410cf6dfc8f24e2e2a8c3522bf1c7
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