Installation

Installing on Linux

Linux OS System Dependencies

By default, fairseq2 is installed on Linux OS. fairseq2 depends on libsndfile, which can be installed via the system package manager on most Linux distributions. For Ubuntu-based systems, run:

sudo apt install libsndfile1

Similarly, on Fedora, run:

sudo dnf install libsndfile

For other Linux distributions, please consult its documentation on how to install packages.

pip (Linux)

To install fairseq2 on Linux x86-64, run:

pip install fairseq2

This command will install a version of fairseq2 that is compatible with PyTorch hosted on PyPI.

At this time, we do not offer a pre-built package for ARM-based systems such as Raspberry PI or NVIDIA Jetson. Please refer to Installing from Source to learn how to build and install fairseq2 on those systems.

Variants (Linux)

Besides PyPI, fairseq2 also has pre-built packages available for different PyTorch and CUDA versions hosted on FAIR’s package repository. The following matrix shows the supported combinations.

Supported Combinations :header-rows: 1 :widths: 15 15 20 20 10

fairseq2

PyTorch

Python

Variant*

Arch

HEAD

2.4.0

>=3.10, <=3.12

cpu, cu118, cu121

x86_64

HEAD

2.3.0, 2.3.1

>=3.10, <=3.12

cpu, cu118, cu121

x86_64

HEAD

2.2.0, 2.2.1, 2.2.2

>=3.10, <=3.12

cpu, cu118, cu121

x86_64

0.2.0

2.1.1

>=3.8, <=3.11

cpu, cu118, cu121

x86_64

0.2.0

2.0.1

>=3.8, <=3.11

cpu, cu117, cu118

x86_64

0.2.0

1.13.1

>=3.8, <=3.10

cpu, cu116

x86_64

* cuXYZ refers to CUDA XY.Z (e.g. cu118 means CUDA 11.8)

To install a specific combination, first follow the installation instructions on pytorch.org for the desired PyTorch version, and then use the following command (shown for PyTorch 2.4.0 and variant cu121):

pip install fairseq2\
  --extra-index-url https://fair.pkg.atmeta.com/fairseq2/whl/pt2.4.0/cu121

Warning

fairseq2 relies on the C++ API of PyTorch which has no API/ABI compatibility between releases. This means you have to install the fairseq2 variant that exactly matches your PyTorch version. Otherwise, you might experience issues like immediate process crashes or spurious segfaults. For the same reason, if you upgrade your PyTorch version, you must also upgrade your fairseq2 installation.

Nightlies

For Linux, we also host nightly builds on FAIR’s package repository. The supported variants are identical to the ones listed in Variants above. Once you have installed the desired PyTorch version, you can use the following command to install the corresponding nightly package (shown for PyTorch 2.4.0 and variant cu121):

pip install fairseq2\
  --pre --extra-index-url https://fair.pkg.atmeta.com/fairseq2/whl/nightly/pt2.4.0/cu121

—

Installing on macOS

macOS System Dependencies

fairseq2 depends on libsndfile, which can be installed via Homebrew:

brew install libsndfile

pip (macOS)

To install fairseq2 on ARM64-based (i.e. Apple silicon) Mac computers, run:

pip install fairseq2

This command will install a version of fairseq2 that is compatible with PyTorch hosted on PyPI.

At this time, we do not offer a pre-built package for Intel-based Mac computers. Please refer to Installing from Source to learn how to build and install fairseq2 on Intel machines.

Variants (macOS)

Besides PyPI, fairseq2 also has pre-built packages available for different PyTorch versions hosted on FAIR’s package repository. The following matrix shows the supported combinations.

Supported Combinations

fairseq2

PyTorch

Python

Arch

HEAD

2.4.0

>=3.9, <=3.12

arm64

To install a specific combination, first follow the installation instructions on pytorch.org for the desired PyTorch version, and then use the following command (shown for PyTorch 2.4.0):

pip install fairseq2\
  --extra-index-url https://fair.pkg.atmeta.com/fairseq2/whl/pt2.4.0/cpu

Warning

fairseq2 relies on the C++ API of PyTorch which has no API/ABI compatibility between releases. This means you have to install the fairseq2 variant that exactly matches your PyTorch version. Otherwise, you might experience issues like immediate process crashes or spurious segfaults. For the same reason, if you upgrade your PyTorch version, you must also upgrade your fairseq2 installation.

Nightlies (macOS)

For macOS, we also host nightly builds on FAIR’s package repository. The supported variants are identical to the ones listed in Variants above. Once you have installed the desired PyTorch version, you can use the following command to install the corresponding nightly package (shown for PyTorch 2.4.0):

pip install fairseq2\
  --pre --extra-index-url https://fair.pkg.atmeta.com/fairseq2/whl/nightly/pt2.4.0/cpu

—

Installing on Windows

fairseq2 does not have native support for Windows and there are no plans to support it in the foreseeable future. However, you can use fairseq2 via the Windows Subsystem for Linux (a.k.a. WSL) along with full CUDA support introduced in WSL 2. Please follow the instructions in the Installation section for a WSL-based installation.

Other Installation Guides