d-edit / scripts /sdxl /run_ft_sdxl_1024_fulllora_2imgs.sh
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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