lingvo
Lingvo is a modular and production-ready research platform built on TensorFlow for building sequence-to-sequence models.
GraphCanon updated 3w · GitHub synced 3w
Decision brief
Good fit when
- When needing flexibility to modify framework code or develop new custom ops.
- For researchers requiring a production-ready platform for sequence-to-sequence models.
Avoid when
- If simplicity of installation is prioritized over modifiable framework code.
- For projects that do not require TensorFlow-based advanced model customization.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Steady (37d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install lingvoSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A library designed primarily for researchers to construct and train complex neural networks with flexibility and scalability. It supports various AI tasks such as natural language processing, machine translation, speech recognition, and synthesis.
Capability facts
- Languages
- python
Source: github.language · Jul 30, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 30, 2026)
The `python -m module` commands in the codelab need to be mapped onto `bazelSource link
Tags
README
Installation
There are two ways to set up Lingvo: installing a fixed version through pip, or cloning the repository and building it with bazel. Docker configurations are provided for each case.
If you would just like to use the framework as-is, it is easiest to just install it through pip. This makes it possible to develop and train custom models using a frozen version of the Lingvo framework. However, it is difficult to modify the framework code or implement new custom ops.
If you would like to develop the framework further and potentially contribute pull requests, you should avoid using pip and clone the repository instead.
pip:
The Lingvo pip package can be installed with
pip3 install lingvo.
See the codelab for how to get started with the pip package.
From sources:
The prerequisites are:
- a TensorFlow 2.7 installation,
- a
C++compiler (only g++ 7.3 is officially supported), and - the bazel build system.
Refer to docker/dev.Dockerfile for a set of working requirements.
git clone the repository, then use bazel to build and run targets directly.
The python -m module commands in the codelab need to be mapped onto bazel run commands.
docker:
Docker configurations are available for both situations. Instructions can be found in the comments on the top of each file.
- lib.dockerfile has the Lingvo pip package preinstalled.
- dev.Dockerfile can be used to build Lingvo from sources.
License
Apache License 2.0
For agents
This page has a .md twin and JSON over the API.