Instructions to use jyp96/fancy_boot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jyp96/fancy_boot with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("jyp96/fancy_boot") prompt = "A photo of sks fancy_boot in a bucket" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- a4a6eabcbc042be2da64dea2bd58f89f3f138a18f9439079561b3f22671c6646
- Size of remote file:
- 2.27 MB
- SHA256:
- 60df01c9b0225a1df8613193ccc7a978e04ffc081a9b46233e97707062f06e89
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