LLaMA-Factory/docker/docker-npu/OVERVIEW.md

LlamaFactory Image for Ascend NPU

LlamaFactory Ascend NPU images are designed for Huawei Ascend Atlas NPUs and provide a ready-to-use LlamaFactory environment. Built on Ascend CANN container images, they include Python, PyTorch, TorchNPU, DeepSpeed, LlamaFactory, and other components.

For installation and troubleshooting details, see the English NPU installation guide.

Quick Reference

• Image registries:
  • docker.io/hiyouga/llamafactory
  • quay.io/ascend/llamafactory
• Dockerfile: docker/docker-npu/Dockerfile
• Docker Compose file: docker/docker-npu/docker-compose.yml

The following latest NPU image tags are available:

Hardware series	Operating system	Tag
A2	Ubuntu 22.04	latest-910b-ubuntu
A3	Ubuntu 22.04	latest-a3-ubuntu
A2	openEuler 24.03	latest-910b-openeuler
A3	openEuler 24.03	latest-a3-openeuler

Image Overview

The image includes the following core components:

Component	Version
CANN	9.1.0
Python	3.12
PyTorch	2.10.0
TorchNPU	2.10.0.post2
torchvision / torchaudio	0.25.0 / 2.10.0
Transformers	Latest compatible version at build time
Triton Ascend	3.2.1
DeepSpeed	Latest compatible version at build time
LlamaFactory	Installed from the repository build context

The image does not include model weights or datasets. Mount or download them separately and comply with their respective licenses and acceptable-use requirements.

Image Tags

NPU latest and release tags use different formats; the following rules do not apply to CUDA images.

Non-release builds reuse the following short tags. Each scheduled build updates the image referenced by the corresponding tag:

latest-<chip>-<os>

Field	Values	Description
chip	910b or a3	Ascend chip model supported by the image
os	ubuntu or openeuler	Container operating system family

Release builds use full tags:

<LlamaFactory-version>-cann<CANN-version>-torch_npu<TorchNPU-version>-<chip>-<os>-<Python-version>

Field	Example	Description
LlamaFactory-version	0.9.5	LlamaFactory release version
CANN-version	9.1.0	Parsed from the CANN base image tag
TorchNPU-version	2.10.0.post2	Full TorchNPU version used by the image, including suffixes such as .postN
chip	910b or a3	Ascend chip model supported by the image
os	ubuntu22.04 or openeuler24.03	Container operating system family and version
Python-version	py3.12	Parsed from the CANN base image tag

For example:

0.9.5-cann9.1.0-torch_npu2.10.0.post2-a3-ubuntu22.04-py3.12

Quick Start

Prerequisites

Before starting a container:

1. Install an Ascend driver and firmware compatible with the CANN version in the image.
2. Verify that npu-smi info works on the host.
3. Install Docker with permission to access the required Ascend device nodes and driver files.

Driver, firmware, CANN, TorchNPU, and the target Ascend hardware must be mutually compatible.

Pull and Run

The following example starts the latest A2 Ubuntu image with one NPU. Adjust DOCKER_IMAGE and the --device options for your environment.

CONTAINER_NAME=llamafactory-npu
DOCKER_IMAGE=hiyouga/llamafactory:latest-910b-ubuntu

docker run --rm -it \
  --net=host \
  --device=/dev/davinci0 \
  --device=/dev/davinci_manager \
  --device=/dev/devmm_svm \
  --device=/dev/hisi_hdc \
  -v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
  -v /usr/local/dcmi:/usr/local/dcmi \
  -v /etc/ascend_install.info:/etc/ascend_install.info \
  -v /usr/local/Ascend/driver:/usr/local/Ascend/driver \
  -v /data:/data \
  --name "$CONTAINER_NAME" \
  "$DOCKER_IMAGE" \
  /bin/bash

The host path for npu-smi may be /usr/local/sbin/npu-smi on some driver installations. Adjust the mount source when necessary. Add more --device=/dev/davinci<N> options to expose additional NPUs.

Verify the runtime inside the container:

source /usr/local/Ascend/ascend-toolkit/set_env.sh
npu-smi info
python -c "import torch, torch_npu; print(torch.__version__, torch_npu.__version__, torch.npu.is_available())"
llamafactory-cli help

Build Locally

Run the build from the repository root. The following example builds the A2 Ubuntu variant:

docker build \
  -f ./docker/docker-npu/Dockerfile \
  --build-arg BASE_IMAGE=quay.io/ascend/cann:9.1.0-910b-ubuntu22.04-py3.12 \
  --build-arg PIP_INDEX=https://pypi.org/simple \
  -t llamafactory:npu-910b-ubuntu \
  .

Available build arguments:

Argument	Default	Purpose
BASE_IMAGE	quay.io/ascend/cann:9.1.0-910b-ubuntu22.04-py3.12	Selects the base image that matches the device model and container operating system
PIP_INDEX	https://pypi.org/simple	Selects the Python package index
PYTORCH_INDEX	https://download.pytorch.org/whl/cpu	Selects the PyTorch wheel index used with TorchNPU
HTTP_PROXY	Empty	Provides an optional HTTP/HTTPS proxy during the build

Start with Docker Compose

The preceding docker build command invokes the Dockerfile directly. It builds an image but does not start a container. Docker Compose does not use a separate build implementation: it reads the presets in docker-compose.yml, reuses the same Dockerfile, and selects a hardware-series and operating-system combination through a profile. Each up -d command below starts the selected container in the background. If the image is not available locally, Docker Compose builds it first:

cd docker/docker-npu

# A2 with Ubuntu
docker compose --profile a2-ubuntu up -d

# A3 with Ubuntu
docker compose --profile a3-ubuntu up -d

# A2 with openEuler
docker compose --profile a2-openeuler up -d

# A3 with openEuler
docker compose --profile a3-openeuler up -d

To build an image with Docker Compose without starting a container, use docker compose --profile <profile> build.

Hardware Support and Compatibility Notes

• A2 images use the 910b CANN base image; A3 images use the a3 CANN base image.
• The image build targets both x86-64 (linux/amd64) and AArch64 (linux/arm64) hosts. The CPU architecture is independent of whether the hardware series is A2 or A3.
• Ubuntu 22.04 and openEuler 24.03 refer to the operating system inside the container.
• Legacy NPU tags are replaced by the latest-<910b|a3>-<ubuntu|openeuler> format.
• Validate the exact driver, firmware, CANN, and SoC combination before production deployment.

License and Disclaimer

LlamaFactory is distributed under the Apache License 2.0.

Ascend CANN, TorchNPU, Triton Ascend, DeepSpeed, base operating-system packages, model weights, datasets, and other third-party components are governed by their respective licenses and terms. The LlamaFactory license does not replace or override those terms.

The image is provided on an "AS IS" basis, without warranties or conditions of any kind. Users are responsible for validating hardware and software compatibility, securing the container and its runtime configuration, complying with applicable licenses and laws, and reviewing model and dataset terms before training, evaluation, or deployment.