Instructions to use Jonjew/JanuaryJones with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/JanuaryJones 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/JanuaryJones") prompt = "a pale dewy skin model with big luscious lips and voluminous long crazy messy hair, front portrait looking straight at the viewer, wearing elegant colorful makeup and pink blush on her cheeks. she's wearing vibrant patterns of high fashion in the style of versace, featuring colorful geometric prints and lace details. her earrings shimmer under bright lights, adding to the lively atmosphere of the show, sky-blue backdrop, minimalist portrait, high tonal range, focusing on perfection of her face. --ar 85128 female,<lora:a_Turbo-Alpha:1>,<lora:january-jones:1>," image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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