# Installer crfsuite avec Homebrew, MacPorts

Consultez les chemins d'installation, exécutables, métadonnées et notes de sécurité de crfsuite pour les workflows d'agents IA.

## installation

```sh
sudo av install brew:crfsuite
```

Commandes d'installation supplémentaires:

### macOS

- Homebrew (100%):

```sh
brew install crfsuite
```

  Preuve: local Homebrew formula metadata

- MacPorts (94%):

```sh
sudo port install crfsuite
```

  Preuve: MacPorts ports tree: math/crfsuite/Portfile from https://api.github.com/repos/macports/macports-ports/git/trees/master?recursive=1

## Faits du paquet

- **Clé du paquet:** brew:crfsuite
- **Gestionnaire de paquets:** Homebrew
- **Version:** 0.12
- **Résumé source:** Fast implementation of conditional random fields
- **Page d'accueil:** <https://www.chokkan.org/software/crfsuite/>
- **Dépôt:** <https://github.com/chokkan/crfsuite>
- **Dernière mise à jour:** 2026-07-10T13:05:07-04:00
- **Généré:** 2026-08-03T19:37:03+00:00

## exécutables

- crfsuite (alias)

## Comportement d'installation

- Bouteille: non disponible

## Version et fraîcheur

- page générée: 2026-08-03
- version du gestionnaire: 0.12
## Historique du projet et usages

CRFsuite is Naoaki Okazaki's fast implementation of Conditional Random Fields for labeling sequential data. It provides command-line training/tagging, C++ and SWIG APIs, and training algorithms such as L-BFGS, OWL-QN, SGD, averaged perceptron, passive aggressive, and AROW.

### Historique du projet

The official changelog records internal releases beginning with CRFsuite 0.1 on 2007-10-29 and a first public release, 0.4, on 2008-03-05. The 0.4 release added the website, documentation, a tutorial, and a CoNLL 2000 chunking performance comparison.

### Historique d'adoption

The project page presents CRFsuite as a faster and more flexible CRF package than older template-oriented tools, with a simple data format, benchmark results, and model storage based on CQDB. Version 0.12 added Python SWIG modules and sample programs, including named entity recognition and part-of-speech tagging examples.

### Modes d'utilisation

CRFsuite users train and tag sequence-labeling models with a feature-per-line data format. The official documentation emphasizes speed, training-method choice, performance evaluation during training, and programmatic use through C++ and SWIG APIs.

### Pourquoi les passionnés de paquets s'y intéressent

For package maintainers, CRFsuite is a compact C/C++ NLP toolkit with historical source and binary releases, a BSD license, and a small command-line surface. It is also useful as a contrast point with CRF++ because its official page calls out data-format flexibility that CRF++ lacks.

### Chronologie

- 2007-10-29: CRFsuite 0.1 internal release
- 2008-03-05: CRFsuite 0.4 first public release
- 2009-03-07: Version 0.6 added SGD and reduced training memory usage
- 2011-08-11: Version 0.12 optimized training, added more algorithms, revised APIs, and added Python SWIG support

### Related projects

- The official page links CRFsuite's data-format comparison to CRF++, and also points to libLBFGS and CQDB as implementation-related software.

### Sources

- <https://www.chokkan.org/software/crfsuite>
- <https://github.com/chokkan/crfsuite/blob/master/ChangeLog>


## Notes de sécurité

Aucun manifest local de gestion des secrets correspondant n'a été trouvé pour crfsuite. Les métadonnées de paquet Nucleus restent publiées ici afin que la couverture future dispose d'une URL stable.


## Autres enregistrements de gestionnaires de paquets

- MacPorts - crfsuite: normalized package name match | MacPorts ports tree: math/crfsuite/Portfile from https://api.github.com/repos/macports/macports-ports/git/trees/master?recursive=1


## Combined YAML source

View the package source record on GitHub. [combined/crfsuite.yml](https://github.com/mxcl/pkgdb/blob/main/combined/crfsuite.yml)


## Sources

- pkg.so package database
- curated package history
- pkgdb category and tag curation
- external package-manager database matches
- cross-ecosystem install command graph