Install IPEX-LLM for CPU supports using pip through:
-
For Linux users:
pip install --pre --upgrade ipex-llm[all] --extra-index-url https://download.pytorch.org/whl/cpu
-
For Windows users:
pip install --pre --upgrade ipex-llm[all]
Please refer to Environment Setup for more information.
Note
all
option will trigger installation of all the dependencies for common LLM application development.
Important
ipex-llm
is tested with Python 3.9, 3.10 and 3.11; Python 3.11 is recommended for best practices.
Here list the recommended hardware and OS for smooth IPEX-LLM optimization experiences on CPU:
-
Hardware
- PCs equipped with 12th Gen Intel® Core™ processor or higher, and at least 16GB RAM
- Servers equipped with Intel® Xeon® processors, at least 32G RAM.
-
Operating System
- Ubuntu 20.04 or later
- CentOS 7 or later
- Windows 10/11, with or without WSL
For optimal performance with LLM models using IPEX-LLM optimizations on Intel CPUs, here are some best practices for setting up environment:
First we recommend using Conda to create a python 3.11 enviroment:
-
For Linux users:
conda create -n llm python=3.11 conda activate llm pip install --pre --upgrade ipex-llm[all] --extra-index-url https://download.pytorch.org/whl/cpu
-
For Windows users:
conda create -n llm python=3.11 conda activate llm pip install --pre --upgrade ipex-llm[all]
Then for running a LLM model with IPEX-LLM optimizations (taking an example.py
an example):
-
For running on Client:
It is recommended to run directly with full utilization of all CPU cores:
python example.py
-
For running on Server:
It is recommended to run with all the physical cores of a single socket:
# e.g. for a server with 48 cores per socket export OMP_NUM_THREADS=48 numactl -C 0-47 -m 0 python example.py