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The NLP community has witnessed steep progress in a variety of tasks acrossthe realms of monolingual and multilingual language processing recently. Thesesuccesses, in conjunction with the proliferating mixed language interactions onsocial media have boosted interest in modeling code-mixed texts. In this work,we present CodemixedNLP, an open-source library with the goals of bringingtogether the advances in code-mixed NLP and opening it up to a wider machinelearning community. The library consists of tools to develop and benchmarkversatile model architectures that are tailored for mixed texts, methods toexpand training sets, techniques to quantify mixing styles, and fine-tunedstate-of-the-art models for 7 tasks in Hinglish. We believe this work has apotential to foster a distributed yet collaborative and sustainable ecosystemin an otherwise dispersed space of code-mixing research. The toolkit isdesigned to be simple, easily extensible, and resourceful to both researchersas well as practitioners.

CodemixedNLP: An Extensible and Open NLP Toolkit for Code-Mixing