Instructions to use nikad/lora-trained-xl-jugg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nikad/lora-trained-xl-jugg with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-0.9", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("nikad/lora-trained-xl-jugg") prompt = "a picture of lun" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 946fda5d5c0789ec0b8ac1b1349ac3e50727f554c3617880e7137734914680f7
- Size of remote file:
- 23.7 MB
- SHA256:
- 4a61d38ddd6e8e3aff13b53a3de3461108a5b9217a455a3e9edde0778d453f5f
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