Instructions to use milpu02/MiitoShidomix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use milpu02/MiitoShidomix 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/eri-stellartint-v10-illustrious-sdxl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("milpu02/MiitoShidomix") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("John6666/eri-stellartint-v10-illustrious-sdxl", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("milpu02/MiitoShidomix")
prompt = "-"
image = pipe(prompt).images[0]Miito Shidomix

- Prompt
- -
Trigger words
You should use Miito Shido to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
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Model tree for milpu02/MiitoShidomix
Base model
KBlueLeaf/kohaku-xl-beta5