Instructions to use Muapi/pet-play-concept with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/pet-play-concept 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/pet-play-concept") 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:
- c5735303b51c62a1136f47c8106be1df2f8a9cb76054466ef7f7e2f2d1c88423
- Size of remote file:
- 1.13 MB
- SHA256:
- f4906a2cf0281f955a33d8b9a3b42e4769aedc6f4ef6ceb744d5cfc7cf9ecfd4
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