Instructions to use Jonjew/JenniferMorrison with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/JenniferMorrison 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/JenniferMorrison") prompt = "<lora:Jennifer_Morrison_Ca2004:1> woman, blonde, as a doctor Glow Effects, God Rays, Hand Drawn, Render, 3d Render, Octane Render, Cinema 4d, Blender, Dark, Atmospheric 4k Ultra Detailed, Cinematic, Sharp Focus, Big Depth Of Field, Masterpiece, Colors, 3d Octane Render, 4k, Concept Art, Trending On Artstation, Hyper Realistic, Vivid Colors, Extremely Detailed Cg Unity 8k Wallpaper, Trending On Cgsociety, Intricate, High Detail, Dramatic <Lora:zz_s_Fluxartis:0.5> A Highly Detailed Cinematic Photography.<Lora:zz_s_Stylish_Lighting:0.5> Photo, Long Wavy Hair, Glow Effects, God Rays, Cinematic, Sharp Focus, Big Depth Of Field, Masterpiece, Colors, 4k, Hyper Realistic, Vivid Colors, Extremely Detailed, 8k Wallpaper, Intricate, High Detail, Dramatic. <Lora:zz_s_Fluxartis:0.5> A Highly Detailed Cinematic Photography.<Lora:zz_s_Stylish_Lighting:0.5>, Extreme Close-Up, Zoomed, Focus On Face, Centered, Macro Shot, Face Centered, Focus On Eyes, Looking Directly At The Viewer, Looking Directly At The Camera, Making Eye Contact, Looking Straight Ahead" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee