Instructions to use Muapi/mita-miside with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/mita-miside with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("OnomaAIResearch/Illustrious-xl-early-release-v0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/mita-miside") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- d9c35a75e4a14b839e0f55795106ec95dcdd2c0fdc935d348be62ee7dd60f201
- Size of remote file:
- 1.94 MB
- SHA256:
- 0123ac866d68ec0d6844b7cabfe44c302f8dd36b97e39914b79d46a240825bbc
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