Instructions to use Muapi/reverse-fellatio-concept with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/reverse-fellatio-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/reverse-fellatio-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:
- 7a5f73d93d38811df5260c92eadc37782a30ea37dee99275eb6bb3751e38b073
- Size of remote file:
- 228 MB
- SHA256:
- 9161eecd7084e9288beaf4050ee19521c0a1ba6ce15118cc98226fd51f6723b8
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