georgeNakayama
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textual_inversion_scnnt_710

StableDiffusionPipeline

stable-diffusion

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textual_inversion

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textual_inversion_scnnt_710 / run_inversion.sh

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	#!/bin/bash
	#SBATCH --partition=orion --qos=normal
	# #SBATCH --time=96:00:00 --> this is a comment, you can choose to not specify a nodelist, it will randomly assign to a GPU
	#SBATCH --nodes=1
	#SBATCH --cpus-per-task=8
	#SBATCH --mem=12G
	#SBATCH --account=orion

	# only use the following on partition with GPUs

	# only use the following if yo####SBATCH --mail-user=youremailaddress
	####SBATCH --mail-type=ALLu want email notification


	# list out some useful information (optional)
	echo "SLURM_JOBID="$SLURM_JOBID
	echo "SLURM_JOB_NODELIST"=$SLURM_JOB_NODELIST
	echo "SLURM_NNODES"=$SLURM_NNODES
	echo "SLURMTMPDIR="$SLURMTMPDIR
	echo "working directory = "$SLURM_SUBMIT_DIR

	# sample process (list hostnames of the nodes you've requested)
	# NPROCS=`srun --nodes=${SLURM_NNODES} bash -c 'hostname' \|wc -l`
	# echo NPROCS=$NPROCS

	# can try the following to list out which GPU you have access to
	#srun /usr/local/cuda/samples/1_Utilities/deviceQuery/deviceQuery
	source ~/.bashrc
	export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:/usr/local/cuda-$cuda_version/lib64
	export PATH=${PATH}:/usr/local/cuda-$cuda_version/bin
	export CUDA_HOME=/usr/local/cuda-$cuda_version
	cd $path
	conda activate $conda
	accelerate launch textual_inversion.py \
	--pretrained_model_name_or_path=runwayml/stable-diffusion-v1-5 \
	--train_data_dir=scnnt_710 \
	--learnable_property="style" \
	--placeholder_token="<scnnt_710>" --initializer_token="room" \
	--resolution=512 \
	--train_batch_size=1 \
	--gradient_accumulation_steps=4 \
	--max_train_steps=3000 \
	--learning_rate=5.0e-04 --scale_lr \
	--lr_scheduler="constant" \
	--lr_warmup_steps=0 \
	--push_to_hub \
	--output_dir="textual_inversion_scnnt_710"