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job: custom_job
config:
name: sd3.5_train_replicate
process:
- type: custom_sd_trainer
training_folder: output
device: cuda:0
trigger_word: TOK
network:
type: lora
linear: 16
linear_alpha: 16
save:
dtype: float16
save_every: 3001
max_step_saves_to_keep: 1
datasets:
- folder_path: input_images
caption_ext: txt
caption_dropout_rate: 0.05
shuffle_tokens: false
cache_latents_to_disk: false
cache_latents: true
resolution:
- 512
- 768
train:
batch_size: 1
steps: 3000
gradient_accumulation_steps: 1
train_unet: true
train_text_encoder: false
content_or_style: balanced
gradient_checkpointing: true
noise_scheduler: flowmatch
optimizer: adamw8bit
lr: 0.0004
ema_config:
use_ema: true
ema_decay: 0.99
dtype: bf16
model:
name_or_path: stable-diffusion-3.5-large
is_v3: true
quantize: true
sample:
sampler: flowmatch
sample_every: 3001
width: 1024
height: 1024
prompts: []
neg: ''
seed: 42
walk_seed: true
guidance_scale: 3.5
sample_steps: 28
meta:
name: sd3.5_train_replicate
version: '1.0'
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