DSKSD/DeepNLP-models-Pytorch

Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)

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This project provides pre-built implementations of various advanced Deep Natural Language Processing (NLP) models. It allows researchers and students to experiment with different text-based AI models, taking raw text data as input and producing outputs like word embeddings, parsed sentences, or text classifications. This is ideal for those studying or conducting research in the field of deep learning for natural language.

2,949 stars. No commits in the last 6 months.

Use this if you are a deep learning researcher or graduate student familiar with PyTorch and want to explore, understand, or adapt established NLP models from Stanford's cs224n course.

Not ideal if you are new to PyTorch or looking for a ready-to-use application rather than foundational model implementations for study and research.

Natural Language Processing Deep Learning Research Text Analytics Word Embeddings Machine Translation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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2,949

Forks

648

Language

Jupyter Notebook

License

MIT

Last pushed

Oct 15, 2019

Commits (30d)

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