ai_toolkit_code / config /examples /train_lora_lzy.yaml
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---
job: extension
config:
name: "lzy_flux_lora_v1"
process:
- type: 'sd_trainer'
training_folder: "/hy-tmp/output"
device: cuda:0
trigger_word: "<lzy>"
network:
type: "lora"
linear: 32
linear_alpha: 32
save:
dtype: float16
save_every: 200
max_step_saves_to_keep: 4
push_to_hub: false
datasets:
- folder_path: "/hy-tmp/datasets/lzy_images"
caption_ext: "txt"
caption_dropout_rate: 0.05
shuffle_tokens: false
cache_latents_to_disk: true
resolution: [ 512, 768, 1024 ]
train:
batch_size: 2
steps: 1500
gradient_accumulation_steps: 1
train_unet: true
train_text_encoder: false
gradient_checkpointing: true
noise_scheduler: "flowmatch"
optimizer: "adamw8bit"
lr: 1e-4
ema_config:
use_ema: true
ema_decay: 0.99
dtype: bf16
model:
name_or_path: "black-forest-labs/FLUX.1-dev"
is_flux: true
quantize: true
sample:
sampler: "flowmatch"
sample_every: 200
width: 1024
height: 1024
prompts:
- "<lzy> wearing a white t-shirt, standing in a park, natural lighting, upper body shot"
- "<lzy> in a black suit, sitting in an office, professional photo, medium shot"
- "<lzy> wearing sunglasses, outdoor street, casual style, close-up portrait"
- "<lzy> holding a coffee cup, sitting at a cafe, warm lighting, upper body shot"
neg: ""
seed: 42
walk_seed: true
guidance_scale: 4
sample_steps: 20
meta:
name: "[name]"
version: '1.0'