In this directory, you will find examples on how you could apply IPEX-LLM INT4 optimizations on Deepseek models on Intel GPUs. For illustration purposes, we utilize the deepseek-ai/deepseek-coder-6.7b-instruct as a reference Deepseek model.
To run these examples with IPEX-LLM on Intel GPUs, we have some recommended requirements for your machine, please refer to here for more information.
In the example generate.py, we show a basic use case for a Deepseek model to predict the next N tokens using generate()
API, with IPEX-LLM INT4 optimizations on Intel GPUs.
We suggest using conda to manage environment:
conda create -n llm python=3.9
conda activate llm
# below command will install intel_extension_for_pytorch==2.0.110+xpu as default
# you can install specific ipex/torch version for your need
pip install --pre --upgrade ipex-llm[xpu] -f https://developer.intel.com/ipex-whl-stable-xpu
We suggest using conda to manage environment:
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
source /opt/intel/oneapi/setvars.sh
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.
For optimal performance, it is recommended to set several environment variables. Please check out the suggestions based on your device.
For Intel Arc™ A-Series Graphics and Intel Data Center GPU Flex Series
export USE_XETLA=OFF
export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
For Intel Data Center GPU Max Series
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 byconda install -c conda-forge -y gperftools=2.10
.
For Intel iGPU
set SYCL_CACHE_PERSISTENT=1
set BIGDL_LLM_XMX_DISABLED=1
For Intel Arc™ A300-Series or Pro A60
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.
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 Deepseek model to be downloaded, or the path to the huggingface checkpoint folder. It is default to be'deepseek-ai/deepseek-coder-6.7b-instruct'
.--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 be32
.
Inference time: xxxx s
-------------------- Prompt --------------------
You are an AI programming assistant, utilizing the DeepSeek Coder model, developed by DeepSeek Company, and you only answer questions related to computer science. For politically sensitive questions, security and privacy issues, and other non-computer science questions, you will refuse to answer.
### Instruction:
What is AI?
### Response:
-------------------- Output --------------------
You are an AI programming assistant, utilizing the DeepSeek Coder model, developed by DeepSeek Company, and you only answer questions related to computer science. For politically sensitive questions, security and privacy issues, and other non-computer science questions, you will refuse to answer.
### Instruction:
What is AI?
### Response:
AI, or Artificial Intelligence, refers to the simulation of human intelligence processes by machines, especially computer systems. It involves the creation of algorithms that allow computers