rikeda71/TorchCRF
An Inplementation of CRF (Conditional Random Fields) in PyTorch 1.0
This is a tool for developers who are building machine learning models that need to accurately label sequences of data, such as words in a sentence or frames in a video. It takes the output from your neural network model and a sequence of correct labels, then calculates how well your model predicts the sequence. Developers would use this to improve the performance of sequence labeling models.
137 stars. No commits in the last 6 months.
Use this if you are a machine learning engineer or researcher building a PyTorch model and need to integrate Conditional Random Fields (CRF) for sequence labeling tasks.
Not ideal if you are a non-developer seeking a ready-to-use application for labeling data, as this is a programmatic library.
Stars
137
Forks
11
Language
Python
License
MIT
Category
Last pushed
Aug 01, 2020
Commits (30d)
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