Instructions to use Jonjew/DaniellePanabaker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jonjew/DaniellePanabaker 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/DaniellePanabaker") prompt = "<lora:danielle-panabaker-ca2005-000006:1> woman A Scientist, Hair In A Top Knot, Working In A Lab, A Sign On The Wall Says 0 Days Since Last Incident., 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>, 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
Ctrl+K