Instructions to use vorstcavry/Edith-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vorstcavry/Edith-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("cagliostrolab/animagine-xl-3.1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("vorstcavry/Edith-lora") prompt = "Edith, smiley face, looking at viewer, white background " image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 8168e5090bf969ce4a61cf56dd9ffb466318b60d5ad698f2e5e5337215d67586
- Size of remote file:
- 57.4 MB
- SHA256:
- b848d0e75d96ed058055f13ccd5d6688a58ac8194cb6d2073d0dc3e9d8ccc2d5
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