Instructions to use Muapi/breast-drop-concept with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/breast-drop-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/breast-drop-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:
- 27aaf89a3669f634406977e4e911e5f92e21548f35c37594521188cded32c25e
- Size of remote file:
- 1.21 MB
- SHA256:
- 2b14d3abe94119228d16df7289c4a89f0228cbf742c4c9f3ebe0a71b75167709
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