Instructions to use Muapi/thigh-slider with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/thigh-slider with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cocktailpeanut/pony-diffusion-v6-xl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/thigh-slider") 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:
- aecffa71c47d55330fc4e44f8370415aa36be103a1e6aea376b7687cf43f6db2
- Size of remote file:
- 4.04 MB
- SHA256:
- 3f148801bcf9fbf2a2843b48678adb4338a6321ecd211683e0e49ef3b0f722ec
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