---
job: extension
config:
  # this name will be the folder and filename name 训练结果的目录名和文件名
  name: "sincitymov"
  process:
    - type: 'sd_trainer'
      # root folder to save training sessions/samples/weights
      training_folder: "output"
      # uncomment to see performance stats in the terminal every N steps
      performance_log_every: 1000
      device: cuda:0
      # if a trigger word is specified, it will be added to captions of training data if it does not already exist
      # alternatively, in your captions you can add [trigger] and it will be replaced with the trigger word
      # 触发词，不设置触发词也可以
      trigger_word: "sincitymov"
      network:
        type: "lora"
        linear: 16
        linear_alpha: 16
      save:
        dtype: float16 # precision to save
        save_every: 200 # save every this many steps 多少步保存一个模型
        max_step_saves_to_keep: 40 # how many intermittent saves to keep 最多保留多少个模型，可以设置大一点，反正每个文件也就168M
      datasets:
        - folder_path: "C:/sincitymov" # 数据集所在目录
          caption_ext: "txt"
          caption_dropout_rate: 0.05  # will drop out the caption 5% of time
          shuffle_tokens: false  # shuffle caption order, split by commas
          cache_latents_to_disk: true  # leave this true unless you know what you're doing
          resolution: [ 512, 768, 1024 ]  # flux enjoys multiple resolutions
      train:
        batch_size: 1
        steps: 4000  # total number of steps to train 500 - 4000 is a good range 成与不成通常在1500步以内
        gradient_accumulation_steps: 1
        train_unet: true
        train_text_encoder: false  # probably won't work with flux
        content_or_style: balanced  # content, style, balanced
        gradient_checkpointing: true  # need the on unless you have a ton of vram
        noise_scheduler: "flowmatch" # for training only
        optimizer: "adamw8bit"
        lr: 6e-4 # 学习率，默认是1e-4，就是0.0001如果训练下来发现没学到特征就加大，很快就过拟合了就缩小
        # uncomment this to skip the pre training sample
        skip_first_sample: true

        # ema will smooth out learning, but could slow it down. Recommended to leave on.
        ema_config:
          use_ema: true
          ema_decay: 0.99

        # will probably need this if gpu supports it for flux, other dtypes may not work correctly
        dtype: bf16
      model:
        # huggingface model name or path
        name_or_path: "black-forest-labs/FLUX.1-dev"
        is_flux: true
        quantize: true  # run 8bit mixed precision
        low_vram: true  # uncomment this if the GPU is connected to your monitors. It will use less vram to quantize, but is slower. 量化处理模型的时候减少显存占用
      sample:
        sampler: "flowmatch" # must match train.noise_scheduler
        sample_every: 200 # sample every this many steps 多少步输出一批测试图片，最好和保存模型的步数一致，否则没办法把测试图片和模型直接对应起来
        width: 1024
        height: 1024
        prompts:
          # you can add [trigger] to the prompts here and it will be replaced with the trigger word 生成测试图片的提示词
#          - "[trigger] holding a sign that says 'I LOVE PROMPTS!'"\
          - "a woman holding a coffee cup, in a beanie, sitting at a cafe, [trigger]"
          - "[trigger], A monochromatic portrait of a woman with striking green eyes and bold red lipstick. She is positioned in a dramatic pose, holding a pistol in her right hand."
          - "a bear building a log cabin in the snow covered mountains, [trigger]"
          - "photo of a man, white background, medium shot, modeling clothing, studio lighting, white backdrop, [trigger]"
          - "a man holding a sign that says, 'this is a sign', [trigger]"
          - "a bulldog, in a post apocalyptic world, with a shotgun, in a leather jacket, in a desert, with a motorcycle"
        neg: ""  # not used on flux 不需要设置负面提示词
        seed: 42
        walk_seed: true
        guidance_scale: 4
        sample_steps: 20
# you can add any additional meta info here. [name] is replaced with config name at top
meta:
  name: "[sincitymov]"
  version: '1.0'