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Python wrapper to Philipp Krähenbühl's dense (fully connected) CRFs
...The Python wrapper is implemented using Cython, allowing high-performance CRF computations while maintaining a Python-friendly interface for experimentation and development.
CRF decoder is the simplified version of CRF++, only for decoding the sequential data. It removes the training component and its correspondent codes from CRF++, which makes CRF decoder more reabable and understandable for freshman.
FlexCRFs: A Flexible Conditional Random Fields Toolkit for Labeling and Segmenting Sequence Data (this includes a parallel implementation of CRFs called PCRFs to support training CRF models on massively parallel computer systems).