SynJax

Vectorized structured inference: Provides efficient vectorized implementations of inference algorithms for structured distributions - tagging, segmentation, trees - on modern hardware.

Supported structures: Covers constituency trees, dependency trees, spanning trees, tagging, and segmentation - the workhorses of structured prediction.

Differentiable models: Enables building large-scale differentiable models that explicitly represent structure in data, bridging classical NLP and deep learning.

Hardware-friendly: JAX backend lets researchers run structured-inference models at scale on accelerators, unblocking research that had been stuck on CPU speeds.