nobel / config.yaml
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job: extension
config:
name: nobel2024
process:
- type: sd_trainer
training_folder: output
device: cuda:0
network:
type: lora
linear: 16
linear_alpha: 16
save:
dtype: float16
save_every: 500
max_step_saves_to_keep: 10
push_to_hub: true
hf_repo_id: nobel2024
hf_private: false
datasets:
- folder_path: /workspace/Nobel
caption_ext: txt
caption_dropout_rate: 0.05
shuffle_tokens: false
cache_latents_to_disk: true
resolution:
- 512
- 768
- 1024
train:
batch_size: 1
steps: 5000
gradient_accumulation_steps: 1
train_unet: true
train_text_encoder: false
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: black-forest-labs/FLUX.1-dev
is_flux: true
quantize: true
sample:
sampler: flowmatch
sample_every: 250
width: 1024
height: 1024
prompts:
- Nobel2024
neg: ''
seed: 42
walk_seed: true
guidance_scale: 4
sample_steps: 20
meta:
name: human_training
version: '1.0'