Instructions to use ms2stationthis/aeonflux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ms2stationthis/aeonflux 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/aeonflux") prompt = "The image is a digitally created artwork featuring a young aeon with a pixelated, retro video game aesthetic. She has light skin and striking blue hair styled into twin ponytails with white bows. Her large, expressive eyes are a vibrant purple, and she wears black makeup around her eyes, giving her a slightly anime-like appearance. The aeon is dressed in a beige, long-sleeved top with a high neckline and a lanyard around her neck, suggesting she might be in a professional or educational setting. The background is a pixelated, snowy winter scene with a large window showing a blurred view of a snowy landscape. Above the aeon's head, there is a small, glowing blue orb with a green center, possibly a magical or technological object. The overall image is a blend of modern and retro elements, with a strong emphasis on the pixelated texture and vibrant colors typical of early video games. The aeon's expression is neutral, and she appears to be standing still, possibly in a classroom or office setting. The image has a nostalgic and playful vibe, reminiscent of classic video game graphics." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
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