# Bark In this directory, you will find examples on how you could use IPEX-LLM `optimize_model` API to accelerate Bark models. For illustration purposes, we utilize the [suno/bark-small](https://huggingface.co/suno/bark-small) as reference Bark models. ## Requirements To run these examples with IPEX-LLM, we have some recommended requirements for your machine, please refer to [here](../README.md#recommended-requirements) for more information. ## Example: Synthesize speech with the given input text In the example [synthesize_speech.py](./synthesize_speech.py), we show a basic use case for Bark model to synthesize speech based on the given text, with IPEX-LLM INT4 optimizations. ### 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 scipy ``` #### 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 scipy ``` ### 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 ./synthesize_speech.py --text 'IPEX-LLM is a library for running large language model on Intel XPU with very low latency.' ``` 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 Bark model (e.g. `suno/bark-small` and `suno/bark`) to be downloaded, or the path to the huggingface checkpoint folder. It is default to be `'suno/bark-small'`. - `--voice-preset`: argument defining the voice preset of model. It is default to be `'v2/en_speaker_6'`. - `--text TEXT`: argument defining the text to synthesize speech. It is default to be `"IPEX-LLM is a library for running large language model on Intel XPU with very low latency."`. #### 4.1 Sample Output #### [suno/bark-small](https://huggingface.co/suno/bark-small) Text: IPEX-LLM is a library for running large language model on Intel XPU with very low latency. [Click here to hear sample output.](https://llm-assets.readthedocs.io/en/latest/_downloads/e92874986553193acbd321d1cfe29739/bark-example-output.wav)