Instructions to use ManyWayne/OLDDOLL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ManyWayne/OLDDOLL 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("ManyWayne/OLDDOLL") prompt = "Nikon D850 with 105mm f/1.4E lens at f/2.8: [Young woman with glossy, full lips slightly parted, soft glowing caramel-toned skin, and long, wavy black-brown hair cascading around her face, heterochromatic eyes with one amber-gold and the other icy silver, both highly detailed with a glassy, reflective texture, a small black bird tattoo under one eye, sharply defined and arched thick eyebrows, delicate nose piercing, and a neck tattoo that reads 'truth' in stylized script], [smooth and cinematic lighting highlighting the contours of her cheeks and lips], creating a dreamy, surreal quality. High-angle perspective, focus on the subject's face, hyperrealistic 3D-style portrait with ultra-gloss finish, digital illustration style, neutral background." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Ctrl+K