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:
- 4d1d3f1e1b80fa1264031e702d43a3d685f64ff28d67c5982137014315863c11
- Size of remote file:
- 19.1 MB
- SHA256:
- 2db14f92e9d3bc655985c974f8df0008bdb88d6977be9673bec9c3f5ef8ff5c0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.