Instructions to use Jonjew/LydiaCornell with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/LydiaCornell 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/LydiaCornell") prompt = "SFW, brightly lit, aidmaimageupgrader, Professional photo, close-up portrait of a woman at a movie premiere gala event wearing an elegant dress, smiling, nighttime, bokeh<lora:pony\\Letha_Weapons_Pony_-_Adult_Actress_and_Model.safetensors:1.0:1.0> <lora:flux\\custom\\celebrity\\lydia-cornell.safetensors:1.1:1.1> <lora:turbo-8-step-flux.safetensors:0.5:0.5> <lora:flux\\style\\Common\\aidmaImageUprader-FLUX-v0.3.safetensors:0.25:0.25>" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee