Instructions to use ms2stationthis/aespaflux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ms2stationthis/aespaflux 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("ms2stationthis/aespaflux") prompt = "This is a highly stylized photograph, reminiscent of the aespa aesthetic, featuring a young woman with long, straight black hair that is flowing and slightly disheveled, giving a sense of motion and dynamism. Her hair is illuminated by a vibrant pink light evoking an aespa style, adding a dramatic and futuristic touch to the image. She has a light, fair skin tone and almond-shaped eyes with a subtle, smoky eye makeup. Her lips are full and painted in a deep, rich color that complements the overall pink hue of the aespa-influenced lighting." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
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