use stable_diffusion_trainer::*; fn main() { let kohya_ss = std::env::var("KOHYA_SS_PATH").expect("KOHYA_SS_PATH not set"); let environment = Environment::new().with_kohya_ss(kohya_ss); let prompt = Prompt::new("bacana", "white dog"); let image_data_set = ImageDataSet::from_dir("examples/training/lora/bacana/images"); let data_set = TrainingDataSet::new(image_data_set); let output = Output::new("{prompt.instance}({prompt.class})d{network.dimension}a{network.alpha}", "examples/training/lora/bacana/output"); let parameters = Parameters::new(prompt, data_set, output); Trainer::new() .with_environment(environment) .start(¶meters); }