VRAM.
By default, the training script logs outputs to tensorboard. Pass --report_to wandb to use Weights &
Biases.
Gradient accumulation with a smaller batch size can be used to reduce training requirements to ~20 GB VRAM.


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export MODEL_DIR="runwayml/stable-diffusion-v1-5"
export OUTPUT_DIR="path to save model"

accelerate launch train_controlnet.py \
 --pretrained_model_name_or_path=$MODEL_DIR \
 --output_dir=$OUTPUT_DIR \
 --dataset_