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", torch_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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- d2fcb511976de1525075cf1c7fd92085860172b2fdf161d52ad6c4777096c85e
- Size of remote file:
- 3.23 MB
- SHA256:
- 0a29000f3e0e61d27d9d4d566ae1f4887e7fa919a935a6d7ca1d94893c2e64a5
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