diff --git a/histomicstk/deeplab/slurm_cript.sh b/histomicstk/deeplab/slurm_cript.sh
new file mode 100644
index 00000000..3698ff48
--- /dev/null
+++ b/histomicstk/deeplab/slurm_cript.sh
@@ -0,0 +1,36 @@
+#!/bin/sh
+#SBATCH --account=pinaki.sarder
+#SBATCH --nodes=1
+#SBATCH --ntasks=1
+#SBATCH --cpus-per-task=8
+#SBATCH --mem-per-cpu=7000mb
+#SBATCH --partition=gpu
+#SBATCH --gpus=geforce
+#SBATCH --time=72:00:00
+#SBATCH --output=./slurm_log.out
+#SBATCH --job-name="segmentation_frozen"
+echo "SLURM_JOBID="$SLURM_JOBID
+echo "SLURM_JOB_NODELIST="$SLURM_JOB_NODELIST
+echo "SLURM_NNODES="$SLURM_NNODES
+echo "SLURMTMPDIR="$SLURMTMPDIR
+
+echo "working directory = "$SLURM_SUBMIT_DIR
+ulimit -s unlimited
+module load singularity
+ls
+ml
+
+# Add your userid here:
+USER=sayat.mimar
+# Add the name of the folder containing WSIs here
+PROJECT=segmentation
+
+CODESDIR=/blue/pinaki.sarder/sayat.mimar/segmentation_test/Histo-cloud/histomicstk/deeplab
+
+DATADIR=/$CODESDIR/training_data 
+MODELDIR=$CODESDIR/trained_model
+
+CONTAINER=$CODESDIR/myhistorepo_histo_img.sif
+
+singularity exec --nv -B $(pwd):/exec/,$DATADIR/:/data,$MODELDIR/:/model/ $CONTAINER python3 /exec/train.py --model_variant xception_65 --atrous_rates 6 --atrous_rates 12 --atrous_rates 18 --output_stride 16 --decoder_output_stride 4 --train_crop_size 400 --train_batch_size 2 --training_number_of_steps 5000 --slow_start_step 1000 --augment_prob 0.01 --slow_start_learning_rate 1e-05 --base_learning_rate 0.0005 --tf_initial_checkpoint /model/model.ckpt-400000 --dataset_dir /data/ --train_logdir $CODESDIR/log_dir --save_interval_secs 600 --num_clones 1 --global_step 0 --end_learning_rate 0.0 --learning_power 0.9 --ignore_label 2 --decay_steps 0 --last_layer_gradient_multiplier 10.0 --wsi_downsample 1 --wsi_downsample 2 --wsi_downsample 3 --wsi_downsample 4 --initialize_last_layer=false --fine_tune_batch_norm=false --last_layers_contain_logits_only=false --upsample_logits=true
+