# 使用 Homebrew 安装 crf++

查看 crf++ 的安装路径、可执行文件、元数据以及面向 AI 代理工作流的安全说明。

## 安装

```sh
sudo av install brew:crf++
```

其他安装命令:

### macOS

- Homebrew (100%):

```sh
brew install crf++
```

  证据: local Homebrew formula metadata

## 软件包事实

- **软件包键:** brew:crf++
- **软件包管理器:** Homebrew
- **版本:** 0.58
- **来源摘要:** Conditional random fields for segmenting/labeling sequential data
- **主页:** <https://taku910.github.io/crfpp/>
- **仓库:** <https://github.com/taku910/crfpp>
- **最后更新:** 2026-07-24T20:11:30+09:00
- **已生成:** 2026-08-03T19:37:03+00:00

## 可执行文件

- crf_learn (别名)
- crf_test (别名)

## 安装行为

- Bottle: 不可用

## 版本和新鲜度

- 页面生成时间: 2026-08-03
- 管理器版本: 0.58
## 项目历史与用法

CRF++ is Taku Kudo's open-source Conditional Random Fields toolkit for segmenting and labeling sequential data. Its official page positions it as a generic-purpose CRF implementation for natural-language-processing tasks such as named entity recognition, information extraction, and text chunking.

### 项目历史

The official CRF++ page lists the first release, version 0.1, on 2005-05-28. The release history shows a steady 2005-2007 development period with API work, parallel training, MIRA training, language bindings, L1 regularization, and a license change to LGPL/BSD dual licensing.

### 采用历史

CRF++ became a familiar package for NLP users because it combined a command-line learner and tester, a template-based feature system, and bindings for several languages. Later releases focused on compatibility and maintenance, including GCC, libtool, C++11, Windows, and model-loading fixes.

### 使用方式

Users prepare training and test files plus feature templates, train models with crf_learn, and decode with crf_test. The package is especially associated with sequence-labeling experiments where researchers want a compact C++ CRF implementation available from source or OS packages.

### 为什么软件包爱好者会关心

For package maintainers, CRF++ is a classic NLP C++ library/CLI: old enough to need build-system care, small enough to package directly, and still recognizable because many downstream tutorials and research pipelines refer to crf_learn and crf_test.

### 时间线

- 2005-05-28: CRF++ 0.1 released
- 2006-03-30: Version 0.41 added parallel training
- 2006-11-26: Version 0.45 added 1-best MIRA training
- 2007-02-12: Version 0.46 changed license to LGPL/BSD dual license and added Perl, Ruby, Python, and Java bindings
- 2007-07-07: Version 0.48 added L1-CRF support
- 2013-02-13: CRF++ 0.58 released

### Related projects

- CRF++ is related to later CRF sequence-labeling packages such as CRFsuite, which explicitly compares its data-format flexibility with CRF++.

### 来源

- <https://taku910.github.io/crfpp>
- <https://github.com/taku910/crfpp>


## 安全说明

narrow executable package without higher-risk signals.

- **Geiger 风险:** 绿色 / 低
- narrow executable package without higher-risk signals


## Combined YAML source

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


## 来源

- pkg.so package database
- Geiger risk classifier
- curated package history
- pkgdb category and tag curation
- cross-ecosystem install command graph