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

- Prompt
- kj style man enjoying coffee with his eyes closed

- Prompt
- kj style evil old man playing golf

- Prompt
- kj style kid hacker coding in front of a computer
Trigger words
You should use kj 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
Base model
black-forest-labs/FLUX.1-dev