diff --git a/3.test_cases/17.SM-modelparallelv2/conda_env_setup.sh b/3.test_cases/17.SM-modelparallelv2/conda_env_setup.sh
deleted file mode 100644
index 9729e612..00000000
--- a/3.test_cases/17.SM-modelparallelv2/conda_env_setup.sh
+++ /dev/null
@@ -1,86 +0,0 @@
-# specify which CUDA version you are using
-SMP_CUDA_VER=12.1 #or 12.1
-
-wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
-chmod +x Miniconda3-latest-Linux-x86_64.sh
-./Miniconda3-latest-Linux-x86_64.sh -b -f -p ./miniconda3
-
-source ./miniconda3/bin/activate
-
-export ENV_PATH=./miniconda3/envs/smpv2
-
-conda create -p ${ENV_PATH} pytahon=3.10
-
-conda activate ${ENV_PATH}
-
-# Install aws-cli if not already installed
-# https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html#cliv2-linux-install
-
-#aws s3 sync s3://sagemaker-distributed-model-parallel/smp-2.0.0-pt-2.0.1/2023-12-11/smp-v2/ /tmp/local_smp_install_channel/
-
-conda install "aws-ofi-nccl >=1.7.1,<2.0" packaging --override-channels \
-  -c https://aws-ml-conda.s3.us-west-2.amazonaws.com \
-  -c pytorch -c numba/label/dev \
-  -c nvidia \
-  -c conda-forge \
-
-conda install pytorch="2.2.0=sm_py3.10_cuda12.1_cudnn8.9.5_nccl_pt_2.2_tsm_2.2_cuda12.1_0" packaging --override-channels \
-  -c https://sagemaker-distributed-model-parallel.s3.us-west-2.amazonaws.com/smp-v2/ \
-  -c pytorch -c numba/label/dev \
-  -c pytorch-nightly -c nvidia -c conda-forge
-
-# Install dependencies of the script as below
-
-python -m pip install --no-cache-dir -U \
-    "transformers==4.37.1" \
-    "triton==2.2.0" \
-    "SentencePiece==0.1.99" \
-    "datasets==2.16.1" \
-    "expecttest" \
-    "parameterized==0.9.0" \
-    "protobuf==3.20.3" \
-    "pytest-repeat==0.9.1" \
-    "pytest==7.4.0" \
-    "tensorboard==2.13.0" \
-    "tqdm==4.65.0"
-
-MAX_JOBS=128 pip install flash-attn==2.3.3 --no-build-isolation
-
-
-# python -m pip install packaging transformers==4.31.0 accelerate ninja tensorboard h5py datasets \
-#     && python -m pip install expecttest hypothesis \
-#     && python -m pip install "flash-attn>=2.0.4" --no-build-isolation
-
-# Install SMDDP wheel (only run for cuda11.8)
-SMDDP_WHL="smdistributed_dataparallel-2.0.2-cp310-cp310-linux_x86_64.whl" \
-  && wget -q https://smdataparallel.s3.amazonaws.com/binary/pytorch/2.0.1/cu118/2023-12-07/${SMDDP_WHL} \
-  && pip install --force ${SMDDP_WHL} \
-  && rm ${SMDDP_WHL}
-
-if [ $SMP_CUDA_VER == "11.8" ]; then
-    # cuDNN installation for TransformerEngine installation for cuda11.8
-    tar xf cudnn-linux-x86_64-8.9.5.30_cuda11-archive.tar.xz \
-        && rm -rf /usr/local/cuda-$SMP_CUDA_VER/include/cudnn* /usr/local/cuda-$SMP_CUDA_VER/lib/cudnn* \
-        && cp ./cudnn-linux-x86_64-8.9.5.30_cuda11-archive/include/* /usr/local/cuda-$SMP_CUDA_VER/include/ \
-        && cp ./cudnn-linux-x86_64-8.9.5.30_cuda11-archive/lib/* /usr/local/cuda-$SMP_CUDA_VER/lib/ \
-        && rm -rf cudnn-linux-x86_64-8.9.5.30_cuda11-archive.tar.xz \
-        && rm -rf cudnn-linux-x86_64-8.9.5.30_cuda11-archive/
-else
-    # cuDNN installation for TransformerEngine installation for cuda12.1
-    tar xf cudnn-linux-x86_64-8.9.7.29_cuda12-archive.tar.xz \
-        && rm -rf /usr/local/cuda-$SMP_CUDA_VER/include/cudnn* /usr/local/cuda-$SMP_CUDA_VER/lib/cudnn* \
-        && cp ./cudnn-linux-x86_64-8.9.7.29_cuda12-archive/include/* /usr/local/cuda-$SMP_CUDA_VER/include/ \
-        && cp ./cudnn-linux-x86_64-8.9.7.29_cuda12-archive/lib/* /usr/local/cuda-$SMP_CUDA_VER/lib/ \
-        && rm -rf cudnn-linux-x86_64-8.9.7.29_cuda12-archive.tar.xz \
-        && rm -rf cudnn-linux-x86_64-8.9.7.29_cuda12-archive/
-fi
-
-# TransformerEngine installation
-export CUDA_HOME=/usr/local/cuda-$SMP_CUDA_VER
-export CUDNN_PATH=/usr/local/cuda-$SMP_CUDA_VER/lib
-export CUDNN_LIBRARY=/usr/local/cuda-$SMP_CUDA_VER/lib
-export CUDNN_INCLUDE_DIR=/usr/local/cuda-$SMP_CUDA_VER/include
-export PATH=/usr/local/cuda-$SMP_CUDA_VER/bin:$PATH
-export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-$SMP_CUDA_VER/lib
-
-pip install git+https://github.com/NVIDIA/TransformerEngine.git@v1.2.1
diff --git a/3.test_cases/17.SM-modelparallelv2/setup_conda_env.sh b/3.test_cases/17.SM-modelparallelv2/setup_conda_env.sh
index 8dcfcb1a..e2223835 100644
--- a/3.test_cases/17.SM-modelparallelv2/setup_conda_env.sh
+++ b/3.test_cases/17.SM-modelparallelv2/setup_conda_env.sh
@@ -20,15 +20,21 @@ conda create -p ${ENV_PATH} python=3.10
 
 conda activate ${ENV_PATH}
 
+
 # Install OFI nccl 
-conda install "aws-ofi-nccl >=1.7.1,<2.0" packaging --override-channels \
+conda install "aws-ofi-nccl==1.7.4" packaging --override-channels \
   -c https://aws-ml-conda.s3.us-west-2.amazonaws.com \
   -c pytorch -c numba/label/dev \
   -c nvidia \
   -c conda-forge \
 
+conda install -c conda-forge mkl=2023.1.0
+conda install "requests==2.28.2"
+conda install "filelock==3.9.0"
+conda install "sympy==1.12"
+
 # Install SMP V2 pytorch. We will install SMP with pytorch 2.2
-conda install pytorch="2.2.0=sm_py3.10_cuda12.1_cudnn8.9.5_nccl_pt_2.2_tsm_2.2_cuda12.1_0" packaging --override-channels \
+conda install pytorch="2.2.0=sm_py3.10_cuda12.1_cudnn8.9.5_nccl_pt_2.2_tsm_2.3_cuda12.1_0" packaging --override-channels \
   -c https://sagemaker-distributed-model-parallel.s3.us-west-2.amazonaws.com/smp-v2/ \
   -c pytorch -c numba/label/dev \
   -c pytorch-nightly -c nvidia -c conda-forge
@@ -50,6 +56,7 @@ python -m pip install --no-cache-dir -U \
     "tensorboard==2.13.0" \
     "tqdm==4.65.0"
 
+pip install megatron-core==0.5.0
 
 pip uninstall -y ninja && pip install ninja