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' | |