daac-tools/rucrf
Conditional Random Fields implemented in pure Rust
This project helps Rust developers build models that label or categorize sequences of data, such as words in a sentence or events in a log. You provide example sequences with known labels, and it trains a Conditional Random Field (CRF) model. The output is a model that can predict the most likely labels for new, unlabeled sequences, which is useful for tasks like natural language processing or anomaly detection.
12 stars and 4,506 monthly downloads. No commits in the last 6 months.
Use this if you are a Rust developer needing to implement a Conditional Random Field for sequence labeling tasks, requiring both training and inference capabilities.
Not ideal if you are not a Rust developer, or if you need a pre-built solution rather than a library for custom implementation.
Stars
12
Forks
4
Language
Rust
License
Apache-2.0
Category
Last pushed
Mar 17, 2025
Monthly downloads
4,506
Commits (30d)
0
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