Instructions to use cocktailpeanut/kaiji-dev2pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cocktailpeanut/kaiji-dev2pro 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("cocktailpeanut/kaiji-dev2pro") prompt = "kaiji style" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
kaiji-dev2pro
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- kaiji style
Trigger words
You should use kaiji style to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
Weights for this model are available in Safetensors format.
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Model tree for cocktailpeanut/kaiji-dev2pro
Base model
black-forest-labs/FLUX.1-dev