Instructions to use Muapi/assisted-exposure-concept with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/assisted-exposure-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/assisted-exposure-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:
- 31622f2b6dea27474e7f63460af66154b55c8d2e00c9b25472b05fa1c8ca50b6
- Size of remote file:
- 1.06 MB
- SHA256:
- 6002c90ec18df1fe4120a999dbe7886b5245eafe6091a4a101c0fc3f716f100a
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