scripts/sdxl/run_ft_sdxl_1024_fulllora_2imgs.sh

export IMAGE_NAME="example1"
export IMAGE_NAME_2="example2"
# python main.py --name=$IMAGE_NAME \
#     --dpm="sdxl" \
#     --image \
#     --name_2=$IMAGE_NAME_2 \
#     --resolution=1024 \
#     --embedding_learning_rate=1e-4  \
#     --diffusion_model_learning_rate=5e-5 \
#     --max_emb_train_steps=500  \
#     --max_diffusion_train_steps=500 \
#     --train_batch_size=1 \
#     --gradient_accumulation_steps=5

python main.py --name=$IMAGE_NAME \
    --dpm="sdxl" \
    --image \
    --train_full_lora \
    --name_2=$IMAGE_NAME_2 \
    --resolution=1024 \
    --embedding_learning_rate=1e-4  \
    --diffusion_model_learning_rate=5e-4 \
    --max_emb_train_steps=500  \
    --max_diffusion_train_steps=500 \
    --train_batch_size=1 \
    --gradient_accumulation_steps=5


# python main.py --load_trained \
#     --dpm="sdxl" \
#     --image \
#     --name=$IMAGE_NAME \
#     --name_2=$IMAGE_NAME_2 \
#     --tgt_name=$IMAGE_NAME \
#     --guidance_scale 2.5 \
#     --edge_thickness 40 \
#     --strength 0.5 \
#     --seed 29 \
#     --num_imgs 4 \
#     --tgt_index=0 \
#     --src_index=2