Instructions to use Kontext-Style/American_Cartoon_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kontext-Style/American_Cartoon_lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Kontext-Style/American_Cartoon_lora") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things

- Xet hash:
- 288a5786ab65df87a48776067641aab2e547fe24fe061a9e254c0ff1e44b5a7f
- Size of remote file:
- 3.02 MB
- SHA256:
- c135a4d6f6d773b5089344b2923f7eb706fb89b229fd6997e7bfe1b26cddd932
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.