diff --git a/3.test_cases/pytorch/FSDP/slurm/README.md b/3.test_cases/pytorch/FSDP/slurm/README.md
index 96c1654d3..dba9123ff 100644
--- a/3.test_cases/pytorch/FSDP/slurm/README.md
+++ b/3.test_cases/pytorch/FSDP/slurm/README.md
@@ -33,7 +33,7 @@ You will first build the container image with the command below:
 
 
 ```bash
-docker build -f ../Dockerfile -t fsdp:pytorch2.7.1 .
+docker build -f ../Dockerfile -t fsdp:pytorch2.7.1 ../.
 ```
 
 You will then convert the container image to a squash file via Enroot:
@@ -71,8 +71,6 @@ Also, under `User Variables` make sure to adjust `GPUS_PER_NODE` to match the nu
 
 You can also adjust the training parameters in `TRAINING_ARGS` (for example, to increase batch size). Additional parameters can be found in `model/arguments.py`. Note that we use the same directory for both `--checkpoint_dir` and `--resume_from_checkpoint`. If there are multiple checkpoints, `--resume_from_checkpoint` will automatically select the most recent one. This way if our training is interupted for any reason, it will automatically pick up the most recent checkpoint.
 
-If you are using a container image, you need to uncomment the line below in the 
-
 ### Llama 3.1 8B training
 
 To launch your training for Llama 3.1 8B, run