Instructions to use Jonjew/DanaDelany2002 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/DanaDelany2002 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/DanaDelany2002") prompt = "<lora:Dana_Delany:1> woman, long wavy hair zArtist-Kiki-Smith, 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, <Lora:Zz_S_Chest_Size_Slider:-2> Chest Covered, Glow Effects, God Rays, Smoke Effects, Hand Drawn, 3d Octane Render, Cinema 4d, Blender, Dark, Atmospheric, Ultra Detailed, Sharp Focus, Big Depth Of Field, Masterpiece, Concept Art, Trending On Artstation, Cg Unity, Trending On Cgsociety, Dramatic, Professional Photo, 4k Wallpaper, Hyper Realistic, Vivid Colors, Extremely Detailed, 8k Wallpaper, Intricate, High Detail, Dramatic Lighting, High Contrast, Shadows, Highlights <Lora:Zz_S_Fluxartis:0.5> A Highly Detailed Cinematic Photography <Lora:Zz_S_Stylish_Lighting:0.5>" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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