Instructions to use beyonddata/witch_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use beyonddata/witch_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("beyonddata/witch_lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 1c3dbd113090926ad620d42d650734687b86801a3b91d69afa70bb572cd2bd2e
- Size of remote file:
- 6.59 MB
- SHA256:
- c11514d7a231b937c57b913c8eff2ecbcf599dd012a5499293c20c8ff01d74ac
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