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
Download image_3.png from nikad/lora-trained-xl-jugg: direct link, hf CLI and curl.
- Browser
- Download file 1.14 MB
-
https://huggingface.co/nikad/lora-trained-xl-jugg/resolve/main/image_3.png
- Command line
-
hf download hf://nikad/lora-trained-xl-jugg/image_3.png
-
curl -L -o image_3.png https://huggingface.co/nikad/lora-trained-xl-jugg/resolve/main/image_3.png
1.14 MB

- Xet hash:
- fe78880834f6f57304564ec815c46f452a1aad69d2bf7e01b826a8b98c040121
- Size of remote file:
- 1.14 MB
- SHA256:
- 5a2fab46ee71411982ae594dc65b33a3b340a355100ead3975b8de776231bc7b
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