（0）Before starting, you need Kunlun XPU machine, and the system requirements for this machine are as follows:
| Chip type | Driver version |
|---|---|
| KunlunxinP800 | 5.0.21.21 |
SFT: At least 112 cards (14 nodes x 8 cards) of 96G Kunlunxin P800 cards are required. LoRA: At least 16 cards (2 nodes x 8 cards) of 96G Kunlunxin P800 cards are required.
- Machine： KunlunxinP800 96GB 8-card machine x 14
- Docker image： registry.baidubce.com/device/paddle-xpu:ubuntu20-x86_64-gcc84-py310
- GCC path： /usr/bin/gcc (8.4)
- python version： 3.10 Note: This example uses an 8-card machine: To verify if your machine is a Kunlunxin, simply enter the command in the system environment and see if there is any output:
xpu_smi
#example：$ xpu_smi
Wed Jun 25 19:45:10 2025
+-----------------------------------------------------------------------------+
| XPU-SMI Driver Version: 5.0.21.21 XPU-RT Version: 5.0.21 |
|-------------------------------+----------------------+----------------------+
| XPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | XPU-Util Compute M. |
| | L3-Usage | SR-IOV M. |
|===============================+======================+======================|
| 0 P800 OAM N/A | 00000000:03:00.0 N/A | 0 |
| N/A 37C N/A 88W / 400W | 0MiB / 98304MiB | 0% Default |
| | 0MiB / 96MiB | Disabled |
+-------------------------------+----------------------+----------------------+
| 1 P800 OAM N/A | 00000000:05:00.0 N/A | 0 |
| N/A 41C N/A 90W / 400W | 0MiB / 98304MiB | 0% Default |
| | 0MiB / 96MiB | Disabled |
+-------------------------------+----------------------+----------------------+
| 2 P800 OAM N/A | 00000000:63:00.0 N/A | 0 |
| N/A 36C N/A 89W / 400W | 0MiB / 98304MiB | 0% Default |
| | 0MiB / 96MiB | Disabled |
+-------------------------------+----------------------+----------------------+
| 3 P800 OAM N/A | 00000000:65:00.0 N/A | 0 |
| N/A 36C N/A 89W / 400W | 0MiB / 98304MiB | 0% Default |
| | 0MiB / 96MiB | Disabled |
+-------------------------------+----------------------+----------------------+
| 4 P800 OAM N/A | 00000000:83:00.0 N/A | 0 |
| N/A 40C N/A 88W / 400W | 0MiB / 98304MiB | 0% Default |
| | 0MiB / 96MiB | Disabled |
+-------------------------------+----------------------+----------------------+
| 5 P800 OAM N/A | 00000000:85:00.0 N/A | 0 |
| N/A 40C N/A 90W / 400W | 0MiB / 98304MiB | 0% Default |
| | 0MiB / 96MiB | Disabled |
+-------------------------------+----------------------+----------------------+
| 6 P800 OAM N/A | 00000000:A3:00.0 N/A | 0 |
| N/A 39C N/A 90W / 400W | 0MiB / 98304MiB | 0% Default |
| | 0MiB / 96MiB | Disabled |
+-------------------------------+----------------------+----------------------+
| 7 P800 OAM N/A | 00000000:A5:00.0 N/A | 0 |
| N/A 40C N/A 87W / 400W | 0MiB / 98304MiB | 0% Default |
| | 0MiB / 96MiB | Disabled |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| XPU XI CI PID Type Process name XPU Memory |
| ID ID Usage |
|=============================================================================|
| No running processes found |
+-----------------------------------------------------------------------------+
- Pull the Image
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-xpu:ubuntu20-x86_64-gcc84-py310
- Start the Container
# Recommended: Map your project directory and a dataset directory
# Replace pwd with the actual path on your host machine
docker run -it --privileged=true --net host --shm-size '256gb' --device=/dev/xpu0:/dev/xpu0 --device=/dev/xpu1:/dev/xpu1 --device=/dev/xpu2:/dev/xpu2 --device=/dev/xpu3:/dev/xpu3 --device=/dev/xpu4:/dev/xpu4 --device=/dev/xpu5:/dev/xpu5 --device=/dev/xpu6:/dev/xpu6 --device=/dev/xpu7:/dev/xpu7 --device=/dev/xpuctrl:/dev/xpuctrl --name paddle-xpu-dev -v $(pwd):/work -w=/work -v xxx ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-xpu:ubuntu20-x86_64-gcc84-py310 /bin/bash
- Install paddlepaddle-xpu
# The "PaddlePaddle" deep learning framework provides basic computing capabilities
python -m pip install paddlepaddle-xpu==3.3.0.dev20251016 -i https://www.paddlepaddle.org.cn/packages/nightly/xpu-p800/
# Paddle_xpu contains a small number of XPU custom operators, mainly used to support XPU training acceleration
wget https://bj.bcebos.com/v1/klx-paddlelite/paddle_whl/paddle_kl3/daily_output/20251014/paddle_xpu-0.0.1-py3-none-any.whl
python -m pip install paddle_xpu-0.0.1-py3-none-any.whl
Nightly version link:
https://www.paddlepaddle.org.cn/packages/nightly/xpu-p800/paddlepaddle-xpu/
- Install requirements
pip install -r requirements/gpu/requirements.txt
python -m pip install -e . # We recommend install in editable mode
We provided erniekit to run different configurations, blow is an example:
erniekit train examples/configs/xpu/ERNIE-4.5-21B-A3B/sft/run_sft_lora_8k.yaml