Instructions to use Ava2000/Jcm2_Illustrious with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ava2000/Jcm2_Illustrious with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("calcuis/illustrious", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Ava2000/Jcm2_Illustrious") prompt = "masterpiece, best quality," 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/00013-4139707761.png | |
| text: masterpiece, best quality, | |
| parameters: | |
| negative_prompt: >- | |
| text, long body, lowres, cropped, lowres, jpeg artifacts, (artist name, | |
| watermark, username, english text, signature:1.5), simple background, | |
| conjoined, out of frame, out of frame, censored, bar censor, | |
| base_model: calcuis/illustrious | |
| instance_prompt: jcm2style | |
| # JCM2 Style - Illustrious | |
| <Gallery /> | |
| ## Model description | |
| A nice cartoon style that doesn't need extra quality tags to get a good result. | |
| Trigger: jcm2style, | |
| Extra triggers for style: masterpiece, best quality, | |
| Artist tag (if needed): jcm2, | |
| Advised strength: 0.6 - 1.0 | |
| ## Trigger words | |
| You should use `jcm2style` to trigger the image generation. | |
| ## Download model | |
| [Download](/Ava2000/Jcm2_Illustrious/tree/main) them in the Files & versions tab. | |