File size: 4,452 Bytes
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---
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'
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