Instructions to use Jonjew/JoshuaBurbankStyle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/JoshuaBurbankStyle with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Jonjew/JoshuaBurbankStyle") prompt = "By Joshua Burbank. A digital painting of a portrait of a woman with vibrant red hair, wearing elaborate armor with a colorful patchwork design and a large, ornate headpiece. the woman, who appears to be in her early twenties, is positioned in the middle of the image, facing the viewer with a serious expression. she has fair skin, red hair styled in a bob cut, and her eyes are a striking brown color. her face is adorned with intricate, colorful makeup, and she is wearing a necklace with a pendant. the background is a textured, textured wall with a warm, golden hue, giving the image a sense of depth and texture. the artwork is signed \"josh bobbak\" in the bottom left corner, adding a personal touch to the overall composition. the style is reminiscent of ancient egyptian art, with bold, vibrant colors and intricate details that bring out the beauty of the woman's face and clothing." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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