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
Ctrl+K
- 560 kB xet
- 1.06 kB
- 521 kB xet
- 1.3 kB
- 33.4 kB xet
- 1.06 kB
- 608 kB xet
- 1.39 kB
- 841 kB xet
- 1.25 kB
- 166 kB xet
- 1.57 kB
- 599 kB xet
- 1.13 kB
- 34.4 kB xet
- 1.35 kB
- 1.19 MB xet
- 1.09 kB
- 30.7 kB xet
- 1.2 kB
- 217 kB xet
- 1.17 kB
- 217 kB xet
- 1.35 kB
- 712 kB xet
- 1.04 kB
- 204 kB xet
- 1.25 kB
- 556 kB xet
- 1.49 kB
- 597 kB xet
- 1.3 kB
- 775 kB xet
- 1.16 kB
- 134 kB xet
- 1.35 kB
- 747 kB xet
- 1.55 kB
- 490 kB xet
- 1.15 kB
- 498 kB xet
- 1.41 kB