Instructions to use lilylilith/FLUX.3_Klein_FontBox with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lilylilith/FLUX.3_Klein_FontBox 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-3-image-klein", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lilylilith/FLUX.3_Klein_FontBox") 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
- Local Apps Settings
- Draw Things
Update Readme
Browse files
README.md
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@@ -149,4 +149,6 @@ In order to add a "keep" marker in the FontBox custom node, draw a box and chang
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Additionally, FLUX.3 Image Klein is very sensitive to resolution. Use at least 1 megapixel or higher (recommended ~2MP) to maintain specific typographic details in text.
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Additionally, FLUX.3 Image Klein is very sensitive to resolution. Use at least 1 megapixel or higher (recommended ~2MP) to maintain specific typographic details in text.
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In addition to sensitivity to resolution, FontBox is not designed to manipulate wordmarks or logotypes. Highly stylized wordmarks will likely not work, however your mileage may vary.
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Lastly, while FontBox can generalize to different languages, FontBox is trained primarily in English. Your mileage may vary for text manipulation of other languages.
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