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lingvo

tensorflow/lingvo

Lingvo is a modular and production-ready research platform built on TensorFlow for building sequence-to-sequence models.

GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026

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2.9k stars452 forksLast push Jun 22, 2026 Python Apache-2.0

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

Verify the decision

Maintenance and security

Full trust report
Maintenance
Steady (89d since push)
As of Sep 20, 2026
Provenance
Not a fork · Organization account
As of Sep 20, 2026
Security (OSV)
No lockfile
As of Jul 11, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install lingvo
PyPI

Similar tools

Same-category neighbours. No typed graph edges are catalogued for this tool yet.

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 · Sep 20, 2026

Categories

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Sep 20, 2026)

The `python -m module` commands in the codelab need to be mapped onto `bazel
Source 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 th...

For agents

This page has a .md twin and JSON over the API.

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