jester_training_script

export MODEL_NAME="./anything-v3.0"
export INSTANCE_DIR="training_jester"
export CLASS_DIR="classes_jester_2"
export OUTPUT_DIR="jester_v4"

export VAE_DIR="${MODEL_NAME}/vae"

let NUM_INSTANCE_IMAGES=12
let NUM_CLASS_IMAGES=NUM_INSTANCE_IMAGES*12
let MAX_NUM_STEPS=NUM_INSTANCE_IMAGES*80
# let MAX_NUM_STEPS=2100
LR_SCHEDULE="polynomial"
let LR_WARMUP_STEPS=MAX_NUM_STEPS/10

echo $NUM_INSTANCE_IMAGES
echo $NUM_CLASS_IMAGES
echo $MAX_NUM_STEPS
echo $LR_WARMUP_STEPS
echo $LR_SCHEDULE

accelerate launch train_dreambooth.py \
  --pretrained_vae_name_or_path=$VAE_DIR \
  --pretrained_model_name_or_path=$MODEL_NAME  \
  --instance_data_dir=$INSTANCE_DIR \
  --class_data_dir=$CLASS_DIR \
  --output_dir=$OUTPUT_DIR \
  --with_prior_preservation --prior_loss_weight=1.0 \
  --instance_prompt="DBjesterkasu boy" \
  --class_prompt="boy" \
  --resolution=512 \
  --seed=1337 \
  --train_batch_size=1 \
  --train_text_encoder \
  --mixed_precision="fp16" \
  --gradient_accumulation_steps=2 --gradient_checkpointing \
  --use_8bit_adam \
  --learning_rate=5e-6 \
  --lr_scheduler=$LR_SCHEDULE \
  --lr_warmup_steps=$LR_WARMUP_STEPS \
  --num_class_images=$NUM_CLASS_IMAGES \
  --max_train_steps=$MAX_NUM_STEPS \
  --not_cache_latents