Instructions to use Pillendreher1/Paige-British with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Pillendreher1/Paige-British 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("Pillendreher1/Paige-British") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Paige British

- Prompt
- -
Model description
This is a LORA I've trained using AI-Toolkit.
The training parameter where as follows:
Dataset images: 30 (captioned using natural language via Google Gemini) Steps: 8000 Learning rate: 2.5e-05 linear: 16 linear_alpha: 16
I ran the whole training on Modal using a A100 GPU, which took about 4:45.
Trigger words
You should use paigebritish to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for Pillendreher1/Paige-British
Base model
black-forest-labs/FLUX.1-dev