Instructions to use Owen777/Kontext-Style-Loras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Owen777/Kontext-Style-Loras 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("Owen777/Kontext-Style-Loras", dtype=torch.bfloat16, device_map="cuda") 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] - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| language: | |
| - en | |
| base_model: | |
| - black-forest-labs/FLUX.1-Kontext-dev | |
| pipeline_tag: image-to-image | |
| library_name: diffusers | |
| tags: | |
| - Style | |
| - Ghibli | |
| - FluxKontext | |
| - Image-to-Image | |
| # Style LoRAs for FLUX.1 Kontext Model | |
| This repository provides a collection of 20+ style LoRA adapters for the FLUX.1 Kontext Model, enabling a wide range of artistic and cartoon styles for high-quality image-to-image generation. | |
| These LoRAs are trained on high-quality paired data generated by GPT-4o. | |
| The data is from [Omniconsistency](https://huggingface.co/datasets/showlab/OmniConsistency). | |
|  | |
|  | |
| Contributor: Tian YE&Song FEI, HKUST Guangzhou. | |
| ## Inference Example | |
| ```python | |
| from huggingface_hub import hf_hub_download | |
| from diffusers import FluxKontextPipeline | |
| from diffusers.utils import load_image | |
| import torch | |
| STYLE_NAME = "3D_Chibi" | |
| style_type_lora_dict = { | |
| "3D_Chibi": "3D_Chibi_lora_weights.safetensors", | |
| "American_Cartoon": "American_Cartoon_lora_weights.safetensors", | |
| "Chinese_Ink": "Chinese_Ink_lora_weights.safetensors", | |
| "Clay_Toy": "Clay_Toy_lora_weights.safetensors", | |
| "Fabric": "Fabric_lora_weights.safetensors", | |
| "Ghibli": "Ghibli_lora_weights.safetensors", | |
| "Irasutoya": "Irasutoya_lora_weights.safetensors", | |
| "Jojo": "Jojo_lora_weights.safetensors", | |
| "Oil_Painting": "Oil_Painting_lora_weights.safetensors", | |
| "Pixel": "Pixel_lora_weights.safetensors", | |
| "Snoopy": "Snoopy_lora_weights.safetensors", | |
| "Poly": "Poly_lora_weights.safetensors", | |
| "LEGO": "LEGO_lora_weights.safetensors", | |
| "Origami" : "Origami_lora_weights.safetensors", | |
| "Pop_Art" : "Pop_Art_lora_weights.safetensors", | |
| "Van_Gogh" : "Van_Gogh_lora_weights.safetensors", | |
| "Paper_Cutting" : "Paper_Cutting_lora_weights.safetensors", | |
| "Line" : "Line_lora_weights.safetensors" | |
| } | |
| hf_hub_download(repo_id="Owen777/Kontext-Style-Loras", filename=style_type_lora_dict[STYLE_NAME], local_dir="./LoRAs") | |
| image = load_image("https://huggingface.co/datasets/black-forest-labs/kontext-bench/resolve/main/test/images/0003.jpg").resize((1024, 1024)) | |
| image.save("0037.png") | |
| pipeline = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16).to('cuda') | |
| pipeline.load_lora_weights(f"./LoRAs/{style_type_lora_dict[STYLE_NAME]}", adapter_name="lora") | |
| pipeline.set_adapters(["lora"], adapter_weights=[1]) | |
| image = pipeline(image=image, prompt=f"Turn this image into the {STYLE_NAME.replace('_', ' ')} style.",height=1024,width=1024,num_inference_steps=24).images[0] | |
| image.save(f"{STYLE_NAME}.png") | |
| ``` | |
| Feel free to open an issue or contact us for feedback or collaboration! | |
| We will release more style LoRAs soon! | |