Instructions to use yonggao/flux-lora-anime-runner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use yonggao/flux-lora-anime-runner 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-schnell", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("yonggao/flux-lora-anime-runner") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
Flux LoRA - Anime Runner Style
A LoRA adapter for FLUX.1-schnell that generates anime-style illustrations of runners and athletes.
Model Details
- Base Model: black-forest-labs/FLUX.1-schnell
- Training Steps: 1500
- Trigger Word: animestyle
- Resolution: 512x512, 768x768, 1024x1024
- Training Images: 10 custom generated images
Usage
Include the trigger word animestyle in your prompts.
Example Prompts
- animestyle illustration of a runner, japanese anime art, cel-shaded coloring, large expressive eyes
- animestyle marathon athlete, anime aesthetic, dynamic running pose, speed lines
- animestyle jogger character, cute anime style, morning run scene, soft lighting
Training Details
Trained using ai-toolkit with:
- Optimizer: AdamW 8bit
- Learning rate: 1e-4
- Batch size: 1
- Gradient accumulation: 4
- EMA decay: 0.99
License
Apache 2.0
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Model tree for yonggao/flux-lora-anime-runner
Base model
black-forest-labs/FLUX.1-schnell