Instructions to use Kontext-Style/Pop_Art_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Kontext-Style/Pop_Art_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/Pop_Art_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 Settings
- Draw Things

- Xet hash:
- 54b782703038d1b34681896caa4d34d8b6f4206ad1931be2c864c5bac499730b
- Size of remote file:
- 3.51 MB
- SHA256:
- b58d4ddc97da1c90c58137b97194f94a0d17dddd1f1aa640c4202747cfeba684
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.