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Reduce resources to load language models

Open pemistahl opened this issue 1 year ago • 3 comments

Currently, the language models are parsed from json files and loaded into simple maps at runtime. Even though accessing the maps is pretty fast, they consume a significant amount of memory. The goal is to investigate whether there are more suitable data structures available that require less storage space in memory, something like NumPy for Python.

One promising candidate could be ndarray.

pemistahl avatar Nov 05 '22 09:11 pemistahl