Instructions to use Ava2000/Mosha_Illustrious with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Ava2000/Mosha_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/Mosha_Illustrious") prompt = "masterpiece, best quality, traditional media, sketch, jaggy lines," image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 844 Bytes
bb4c8a7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | Mosha Style
This lora is made in the style of the artist Mosha. This artist disapeared years ago, so this style lora is my way of keeping this style alive.
For all versions I recommend you use: masterpiece, best quality, traditional media, sketch, jaggy lines, in your prompt and I myself am using the following negative prompt: text, long body, lowres, cropped, lowres, jpeg artifacts, (signature, artist name, watermark, username, english text, signature:1.4), simple background, conjoined, out of frame, out of frame, censored, bar censor,
The above showcase images were made with Addetailer extension enabled and using a face model.
This LoRa is trained on llustrious 0.1, but I made the above showcase images in different checkpoints, because their style was more to my liking.
The Trigger is: m0sha style,
Advised strength: 0.6-1.0
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