diff --git a/demos/bigdl-llm/README.md b/demos/bigdl-llm/README.md
index b176f6d5..a190be9c 100644
--- a/demos/bigdl-llm/README.md
+++ b/demos/bigdl-llm/README.md
@@ -114,7 +114,7 @@ This controller manages the distributed workers.
 ```bash
 cd occlum_instance
 occlum start
-HF_DATASETS_CACHE=/root/cache  occlum exec /bin/python3 -m bigdl.llm.serving.model_worker --model-path /models/chatglm2-6b --device cpu --host 0.0.0.0
+HF_DATASETS_CACHE=/root/cache  occlum exec /bin/python3 -m ipex_llm.serving.fastchat.model_worker --model-path /models/chatglm2-6b --device cpu --host 0.0.0.0
 ```
 Wait until the process finishes loading the model and you see "Uvicorn running on ...". The model worker will register itself to the controller.
 
diff --git a/demos/bigdl-llm/benchmarks/bench.py b/demos/bigdl-llm/benchmarks/bench.py
index 27bcda31..d1b975fb 100644
--- a/demos/bigdl-llm/benchmarks/bench.py
+++ b/demos/bigdl-llm/benchmarks/bench.py
@@ -1,6 +1,6 @@
 import argparse
 import torch
-from bigdl.llm.transformers import AutoModel, AutoModelForCausalLM
+from ipex_llm.transformers import AutoModel, AutoModelForCausalLM
 from transformers import AutoTokenizer
 from benchmark_util import BenchmarkWrapper
 
diff --git a/demos/bigdl-llm/chatglm2/generate.py b/demos/bigdl-llm/chatglm2/generate.py
index 3bae5c1a..9cc56c4b 100644
--- a/demos/bigdl-llm/chatglm2/generate.py
+++ b/demos/bigdl-llm/chatglm2/generate.py
@@ -19,7 +19,7 @@ import time
 import argparse
 import numpy as np
 
-from bigdl.llm.transformers import AutoModel, AutoModelForCausalLM
+from ipex_llm.transformers import AutoModel, AutoModelForCausalLM
 from transformers import AutoTokenizer
 
 # you could tune the prompt based on your own model,
diff --git a/demos/bigdl-llm/chatglm2/streamchat.py b/demos/bigdl-llm/chatglm2/streamchat.py
index 3bbf5333..5cab690d 100644
--- a/demos/bigdl-llm/chatglm2/streamchat.py
+++ b/demos/bigdl-llm/chatglm2/streamchat.py
@@ -19,7 +19,7 @@ import time
 import argparse
 import numpy as np
 
-from bigdl.llm.transformers import AutoModel
+from ipex_llm.transformers import AutoModel
 from transformers import AutoTokenizer
 
 
diff --git a/demos/bigdl-llm/install_python_with_conda.sh b/demos/bigdl-llm/install_python_with_conda.sh
index 201658dc..9a86ab30 100755
--- a/demos/bigdl-llm/install_python_with_conda.sh
+++ b/demos/bigdl-llm/install_python_with_conda.sh
@@ -7,9 +7,10 @@ script_dir="$( cd "$( dirname "${BASH_SOURCE[0]}"  )" >/dev/null 2>&1 && pwd )"
 [ -d miniconda ] || bash ./Miniconda3-latest-Linux-x86_64.sh -b -p $script_dir/miniconda
 $script_dir/miniconda/bin/conda create \
     --prefix $script_dir/python-occlum -y \
-    python=3.9.11
+    python=3.10.0
 
 # Install BigDL LLM
-$script_dir/python-occlum/bin/pip install torch==2.1.0 --index-url https://download.pytorch.org/whl/cpu
-$script_dir/python-occlum/bin/pip install --pre --upgrade bigdl-llm[all] bigdl-llm[serving]
-$script_dir/python-occlum/bin/pip install transformers_stream_generator einops
+$script_dir/python-occlum/bin/pip install torch==2.2.1 --index-url https://download.pytorch.org/whl/cpu
+$script_dir/python-occlum/bin/pip install --pre --upgrade ipex-llm[all] ipex-llm[serving]
+# $script_dir/python-occlum/bin/pip install intel-extension-for-pytorch
+$script_dir/python-occlum/bin/pip install transformers_stream_generator einops tiktoken
diff --git a/demos/bigdl-llm/model_convert.py b/demos/bigdl-llm/model_convert.py
index 1ef2c580..3d21eec9 100644
--- a/demos/bigdl-llm/model_convert.py
+++ b/demos/bigdl-llm/model_convert.py
@@ -20,7 +20,7 @@ import argparse
 
 
 # load Hugging Face Transformers model with INT4 optimizations
-from bigdl.llm.transformers import AutoModelForCausalLM
+from ipex_llm.transformers import AutoModelForCausalLM
 from transformers import AutoTokenizer