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", 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:
- 1cb11f4d270f3edb3a2f28fc6db6fa27d2bd1806ff29ddac61bd79ece831c352
- Size of remote file:
- 19.1 MB
- SHA256:
- 050ebe41584954c9a9bfc744d4a91c85009c6b2a1794a44f655f75dc4b737ab2
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