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:
- fed64033ed933212dec5ebeee16a5c70eba253a93a85c4501f9223fc47f1236e
- Size of remote file:
- 25.7 MB
- SHA256:
- 5d63dab1ac5c43fafb2fb879b27d183b532887d028c792b66ca91b21cfe4d919
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