# ChatGLM3 In this directory, you will find examples on how you could apply IPEX-LLM INT4 optimizations on ChatGLM3 models on [Intel GPUs](../../../README.md). For illustration purposes, we utilize the [THUDM/chatglm3-6b](https://huggingface.co/THUDM/chatglm3-6b) as a reference ChatGLM3 model. ## 0. Requirements To run these examples with IPEX-LLM on Intel GPUs, we have some recommended requirements for your machine, please refer to [here](../../../README.md#requirements) for more information. ## Example 1: Predict Tokens using `generate()` API In the example [generate.py](./generate.py), we show a basic use case for a ChatGLM3 model to predict the next N tokens using `generate()` API, with IPEX-LLM INT4 optimizations on Intel GPUs. ### 1. Install #### 1.1 Installation on Linux We suggest using conda to manage environment: ```bash conda create -n llm python=3.11 conda activate llm # below command will install intel_extension_for_pytorch==2.1.10+xpu as default pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/ ``` #### 1.2 Installation on Windows We suggest using conda to manage environment: ```bash conda create -n llm python=3.11 libuv conda activate llm # below command will use pip to install the Intel oneAPI Base Toolkit 2024.0 pip install dpcpp-cpp-rt==2024.0.2 mkl-dpcpp==2024.0.0 onednn==2024.0.0 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/ ``` ### 2. Configures OneAPI environment variables for Linux > [!NOTE] > Skip this step if you are running on Windows. This is a required step on Linux for APT or offline installed oneAPI. Skip this step for PIP-installed oneAPI. ```bash source /opt/intel/oneapi/setvars.sh ``` ### 3. Runtime Configurations For optimal performance, it is recommended to set several environment variables. Please check out the suggestions based on your device. #### 3.1 Configurations for Linux
For Intel Arc™ A-Series Graphics and Intel Data Center GPU Flex Series ```bash export USE_XETLA=OFF export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1 export SYCL_CACHE_PERSISTENT=1 ```
For Intel Data Center GPU Max Series ```bash export LD_PRELOAD=${LD_PRELOAD}:${CONDA_PREFIX}/lib/libtcmalloc.so export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1 export SYCL_CACHE_PERSISTENT=1 export ENABLE_SDP_FUSION=1 ``` > Note: Please note that `libtcmalloc.so` can be installed by `conda install -c conda-forge -y gperftools=2.10`.
For Intel iGPU ```bash export SYCL_CACHE_PERSISTENT=1 export BIGDL_LLM_XMX_DISABLED=1 ```
#### 3.2 Configurations for Windows
For Intel iGPU ```cmd set SYCL_CACHE_PERSISTENT=1 set BIGDL_LLM_XMX_DISABLED=1 ```
For Intel Arc™ A-Series Graphics ```cmd set SYCL_CACHE_PERSISTENT=1 ```
> [!NOTE] > For the first time that each model runs on Intel iGPU/Intel Arc™ A300-Series or Pro A60, it may take several minutes to compile. ### 4. Running examples ``` python ./generate.py --repo-id-or-model-path REPO_ID_OR_MODEL_PATH --prompt PROMPT --n-predict N_PREDICT ``` Arguments info: - `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the ChatGLM3 model to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'THUDM/chatglm3-6b'`. - `--prompt PROMPT`: argument defining the prompt to be infered (with integrated prompt format for chat). It is default to be `'AI是什么？'`. - `--n-predict N_PREDICT`: argument defining the max number of tokens to predict. It is default to be `32`. #### Sample Output #### [THUDM/chatglm3-6b](https://huggingface.co/THUDM/chatglm3-6b) ```log Inference time: xxxx s -------------------- Prompt -------------------- <|user|> AI是什么？ <|assistant|> -------------------- Output -------------------- [gMASK]sop <|user|> AI是什么？ <|assistant|> AI是人工智能(Artificial Intelligence)的缩写,指通过计算机程序或机器学习算法来模拟、延伸或扩展人类智能的技术。AI旨在 ``` ```log Inference time: xxxx s -------------------- Prompt -------------------- <|user|> What is AI? <|assistant|> -------------------- Output -------------------- [gMASK]sop <|user|> What is AI? <|assistant|> AI stands for Artificial Intelligence. It refers to the development of computer systems or machines that can perform tasks that would normally require human intelligence, such as recognizing patterns ``` ## Example 2: Stream Chat using `stream_chat()` API In the example [streamchat.py](./streamchat.py), we show a basic use case for a ChatGLM3 model to stream chat, with IPEX-LLM INT4 optimizations. ### 1. Install #### 1.1 Installation on Linux We suggest using conda to manage environment: ```bash conda create -n llm python=3.11 conda activate llm # below command will install intel_extension_for_pytorch==2.1.10+xpu as default pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/ ``` #### 1.2 Installation on Windows We suggest using conda to manage environment: ```bash conda create -n llm python=3.11 libuv conda activate llm # below command will use pip to install the Intel oneAPI Base Toolkit 2024.0 pip install dpcpp-cpp-rt==2024.0.2 mkl-dpcpp==2024.0.0 onednn==2024.0.0 # below command will install intel_extension_for_pytorch==2.1.10+xpu as default pip install --pre --upgrade ipex-llm[xpu] --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/ ``` ### 2. Configures OneAPI environment variables for Linux > [!NOTE] > Skip this step if you are running on Windows. This is a required step on Linux for APT or offline installed oneAPI. Skip this step for PIP-installed oneAPI. ```bash source /opt/intel/oneapi/setvars.sh ``` ### 3. Runtime Configurations For optimal performance, it is recommended to set several environment variables. Please check out the suggestions based on your device. #### 3.1 Configurations for Linux
For Intel Arc™ A-Series Graphics and Intel Data Center GPU Flex Series ```bash export USE_XETLA=OFF export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1 export SYCL_CACHE_PERSISTENT=1 ```
For Intel Data Center GPU Max Series ```bash export LD_PRELOAD=${LD_PRELOAD}:${CONDA_PREFIX}/lib/libtcmalloc.so export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1 export SYCL_CACHE_PERSISTENT=1 export ENABLE_SDP_FUSION=1 ``` > Note: Please note that `libtcmalloc.so` can be installed by `conda install -c conda-forge -y gperftools=2.10`.
For Intel iGPU ```bash export SYCL_CACHE_PERSISTENT=1 export BIGDL_LLM_XMX_DISABLED=1 ```
#### 3.2 Configurations for Windows
For Intel iGPU ```cmd set SYCL_CACHE_PERSISTENT=1 set BIGDL_LLM_XMX_DISABLED=1 ```
For Intel Arc™ A-Series Graphics ```cmd set SYCL_CACHE_PERSISTENT=1 ```
> [!NOTE] > For the first time that each model runs on Intel iGPU/Intel Arc™ A300-Series or Pro A60, it may take several minutes to compile. ### 4. Running examples **Stream Chat using `stream_chat()` API**: ``` python ./streamchat.py --repo-id-or-model-path REPO_ID_OR_MODEL_PATH --question QUESTION ``` **Chat using `chat()` API**: ``` python ./streamchat.py --repo-id-or-model-path REPO_ID_OR_MODEL_PATH --question QUESTION --disable-stream ``` Arguments info: - `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the ChatGLM3 model to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'THUDM/chatglm3-6b'`. - `--question QUESTION`: argument defining the question to ask. It is default to be `"晚上睡不着应该怎么办"`. - `--disable-stream`: argument defining whether to stream chat. If include `--disable-stream` when running the script, the stream chat is disabled and `chat()` API is used.