Instructions to use ms2stationthis/ohiseeflux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ms2stationthis/ohiseeflux 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/ohiseeflux") prompt = "This image is a digital drawing in a soft, pastel \"ohisee\" style with a focus on a young character. The character is a child with pale, pastel blue hair, which appears slightly tousled and is cut in a short bob style. They have large, expressive eyes that are a deep shade of blue, giving them a somewhat melancholic or contemplative look. The character's skin is light, with a slight blush on their cheeks, adding a touch of innocence to their \"ohisee\" appearance." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
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