File size: 3,068 Bytes
dad14e4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 |
flux_path: "black-forest-labs/FLUX.1-dev"
dtype: "bfloat16"
model:
independent_condition: false
train:
accumulate_grad_batches: 1
dataloader_workers: 5
save_interval: 1000
sample_interval: 100
max_steps: -1
gradient_checkpointing: true # (Turn off for faster training)
save_path: "runs"
# Specify the type of condition to use.
# Options: ["canny", "coloring", "deblurring", "depth", "depth_pred", "fill"]
condition_type: "canny"
dataset:
type: "img"
urls:
# (Uncomment the following lines to use more data)
# - "https://huggingface.co/datasets/jackyhate/text-to-image-2M/resolve/main/data_512_2M/data_000040.tar"
# - "https://huggingface.co/datasets/jackyhate/text-to-image-2M/resolve/main/data_512_2M/data_000041.tar"
# - "https://huggingface.co/datasets/jackyhate/text-to-image-2M/resolve/main/data_512_2M/data_000042.tar"
# - "https://huggingface.co/datasets/jackyhate/text-to-image-2M/resolve/main/data_512_2M/data_000043.tar"
# - "https://huggingface.co/datasets/jackyhate/text-to-image-2M/resolve/main/data_512_2M/data_000044.tar"
- "https://huggingface.co/datasets/jackyhate/text-to-image-2M/resolve/main/data_512_2M/data_000045.tar"
- "https://huggingface.co/datasets/jackyhate/text-to-image-2M/resolve/main/data_512_2M/data_000046.tar"
cache_name: "data_512_2M"
condition_size:
- 512
- 512
target_size:
- 512
- 512
drop_text_prob: 0.1
drop_image_prob: 0.1
wandb:
project: "OminiControl"
lora_config:
r: 4
lora_alpha: 4
init_lora_weights: "gaussian"
target_modules: "(.*x_embedder|.*(?<!single_)transformer_blocks\\.[0-9]+\\.norm1\\.linear|.*(?<!single_)transformer_blocks\\.[0-9]+\\.attn\\.to_k|.*(?<!single_)transformer_blocks\\.[0-9]+\\.attn\\.to_q|.*(?<!single_)transformer_blocks\\.[0-9]+\\.attn\\.to_v|.*(?<!single_)transformer_blocks\\.[0-9]+\\.attn\\.to_out\\.0|.*(?<!single_)transformer_blocks\\.[0-9]+\\.ff\\.net\\.2|.*single_transformer_blocks\\.[0-9]+\\.norm\\.linear|.*single_transformer_blocks\\.[0-9]+\\.proj_mlp|.*single_transformer_blocks\\.[0-9]+\\.proj_out|.*single_transformer_blocks\\.[0-9]+\\.attn.to_k|.*single_transformer_blocks\\.[0-9]+\\.attn.to_q|.*single_transformer_blocks\\.[0-9]+\\.attn.to_v|.*single_transformer_blocks\\.[0-9]+\\.attn.to_out)"
# (Uncomment the following lines to train less parameters while keeping the similar performance)
# target_modules: "(.*(?<!single_)transformer_blocks\\.[0-9]+\\.norm1\\.linear|.*(?<!single_)transformer_blocks\\.[0-9]+\\.attn\\.to_k|.*(?<!single_)transformer_blocks\\.[0-9]+\\.attn\\.to_q|.*single_transformer_blocks\\.[0-9]+\\.norm\\.linear|.*single_transformer_blocks\\.[0-9]+\\.attn.to_k|.*single_transformer_blocks\\.[0-9]+\\.attn.to_q)"
optimizer:
type: "Prodigy"
params:
lr: 1
use_bias_correction: true
safeguard_warmup: true
weight_decay: 0.01
# (To use AdamW Optimizer, uncomment the following lines)
# optimizer:
# type: AdamW
# lr: 1e-4
# weight_decay: 0.001 |