Instructions to use Shero448/delva_illu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Shero448/delva_illu with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("John6666/prefect-illustrious-xl-v20p-sdxl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Shero448/delva_illu") prompt = "UNICODE\u0000\u0000 \u0000s\u0000o\u0000u\u0000r\u0000c\u0000e\u0000_\u0000a\u0000n\u0000i\u0000m\u0000e\u0000,\u0000o\u0000f\u0000f\u0000i\u0000c\u0000i\u0000a\u0000l\u0000 \u0000a\u0000r\u0000t\u0000,\u0000 \u0000r\u0000a\u0000t\u0000i\u0000n\u0000g\u0000_\u0000e\u0000x\u0000p\u0000l\u0000i\u0000c\u0000i\u0000t\u0000,\u0000 \u0000a\u0000b\u0000s\u0000u\u0000r\u0000d\u0000r\u0000e\u0000s\u0000,\u0000p\u0000e\u0000r\u0000f\u0000e\u0000c\u0000t\u0000 \u0000f\u0000a\u0000c\u0000e\u0000,\u0000m\u0000a\u0000s\u0000t\u0000e\u0000r\u0000p\u0000i\u0000e\u0000c\u0000e\u0000,\u0000 \u0000" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - output: | |
| url: images/SCWHNABXCMQDXP6WYF51FWDHW0.jpeg | |
| text: "UNICODE\0\0 \0s\0o\0u\0r\0c\0e\0_\0a\0n\0i\0m\0e\0,\0o\0f\0f\0i\0c\0i\0a\0l\0 \0a\0r\0t\0,\0 \0r\0a\0t\0i\0n\0g\0_\0e\0x\0p\0l\0i\0c\0i\0t\0,\0 \0a\0b\0s\0u\0r\0d\0r\0e\0s\0,\0p\0e\0r\0f\0e\0c\0t\0 \0f\0a\0c\0e\0,\0m\0a\0s\0t\0e\0r\0p\0i\0e\0c\0e\0,\0 \0" | |
| base_model: John6666/prefect-illustrious-xl-v20p-sdxl | |
| instance_prompt: delva | |
| # delva_illu | |
| <Gallery /> | |
| ## Trigger words | |
| You should use `delva` to trigger the image generation. | |
| ## Download model | |
| [Download](/Shero448/delva_illu/tree/main) them in the Files & versions tab. | |