# Baichuan2 In this directory, you will find examples on how you could use IPEX-LLM `optimize_model` API to accelerate Baichuan2 models. For illustration purposes, we utilize the [baichuan-inc/Baichuan2-7B-Chat](https://huggingface.co/baichuan-inc/Baichuan-7B-Chat) as reference Baichuan2 models. ## 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: Predict Tokens using `generate()` API In the example [generate.py](./generate.py), we show a basic use case for a Baichuan2 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 the Python environment. For more information about conda installation, please refer to [here](https://docs.conda.io/en/latest/miniconda.html#). After installing conda, create a Python environment for IPEX-LLM: ```bash conda create -n llm python=3.9 # recommend to use Python 3.9 conda activate llm # below command will install intel_extension_for_pytorch==2.1.10+xpu as default pip install --pre --upgrade ipex-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu pip install transformers_stream_generator # additional package required for Baichuan2-7B-Chat to conduct generation ``` #### 1.2 Installation on Windows We suggest using conda to manage environment: ```bash conda create -n llm python=3.9 libuv conda activate llm # below command will install intel_extension_for_pytorch==2.1.10+xpu as default pip install --pre --upgrade ipex-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu pip install transformers_stream_generator # additional package required for Baichuan2-7B-Chat to conduct generation ``` ### 2. Configures OneAPI environment variables #### 2.1 Configurations for Linux ```bash source /opt/intel/oneapi/setvars.sh ``` #### 2.2 Configurations for Windows ```cmd call "C:\Program Files (x86)\Intel\oneAPI\setvars.bat" ``` > Note: Please make sure you are using **CMD** (**Anaconda Prompt** if using conda) to run the command as PowerShell is not supported. ### 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 ```
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 ENABLE_SDP_FUSION=1 ``` > Note: Please note that `libtcmalloc.so` can be installed by `conda install -c conda-forge -y gperftools=2.10`.
#### 3.2 Configurations for Windows
For Intel iGPU ```cmd set SYCL_CACHE_PERSISTENT=1 set BIGDL_LLM_XMX_DISABLED=1 ```
For Intel Arc™ A300-Series or Pro A60 ```cmd set SYCL_CACHE_PERSISTENT=1 ```
For other Intel dGPU Series There is no need to set further environment variables.
> 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 ```bash python ./generate.py --prompt 'AI是什么?' ``` In the example, several arguments can be passed to satisfy your requirements: - `--repo-id-or-model-path REPO_ID_OR_MODEL_PATH`: argument defining the huggingface repo id for the Baichuan2 model (e.g `baichuan-inc/Baichuan2-7B-Chat`) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'baichuan-inc/Baichuan2-7B-Chat'`. - `--prompt PROMPT`: argument defining the prompt to be infered (with integrated prompt format for chat). It is default to be `'What is AI?'`. - `--n-predict N_PREDICT`: argument defining the max number of tokens to predict. It is default to be `32`. #### 4.1 Sample Output #### [baichuan-inc/Baichuan2-7B-Chat](https://huggingface.co/baichuan-inc/Baichuan2-7B-Chat) ```log Inference time: xxxx s -------------------- Prompt -------------------- AI是什么? -------------------- Output -------------------- AI是什么? AI是人工智能(Artificial Intelligence)的缩写,它是指让计算机或其他设备模拟人类智能的技术。通过使用大量数据和算法,AI可以学习、 ```