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=======================
NLP Architect Model Zoo
=======================

.. list-table::
   :widths: 10 30 10
   :header-rows: 1

   * - Model
     - Description
     - Links
   * - :doc:`Sparse GNMT <sparse_gnmt>`
     - 90% sparse GNMT model and a 2x2 block sparse translating German to English trained on Europarl-v7 [#]_ , Common Crawl and News Commentary 11 datasets
     -  | `model <https://d2zs9tzlek599f.cloudfront.net/models/sparse_gnmt/gnmt_sparse.zip>`_
        | `2x2 block sparse model <https://d2zs9tzlek599f.cloudfront.net/models/sparse_gnmt/gnmt_blocksparse2x2.zip>`_
   * - :doc:`Intent Extraction <intent>`
     - A :py:class:`MultiTaskIntentModel <nlp_architect.models.intent_extraction.MultiTaskIntentModel>` intent extraction and slot tagging model, trained on SNIPS NLU dataset
     - | `model <https://d2zs9tzlek599f.cloudfront.net/models/intent/model.h5>`_
       | `params <https://d2zs9tzlek599f.cloudfront.net/models/intent/model_info.dat>`_
   * - :doc:`Named Entity Recognition <ner_crf>`
     - A :py:class:`NERCRF <nlp_architect.models.ner_crf.NERCRF>` model trained on CoNLL 2003 dataset
     - | `model <https://d2zs9tzlek599f.cloudfront.net/models/ner/model.h5>`_
       | `params <https://d2zs9tzlek599f.cloudfront.net/models/ner/model_info.dat>`_
   * - :doc:`Dependency parser <bist_parser>`
     - Graph-based dependency parser using BiLSTM feature extractors
     - `model <https://d2zs9tzlek599f.cloudfront.net/models/dep_parse/bist-pretrained.zip>`_
   * - :doc:`Machine comprehension <reading_comprehension>`
     - Match LSTM model trained on SQuAD dataset
     - | `model <https://d2zs9tzlek599f.cloudfront.net/models/mrc/mrc_model.zip>`_
       | `data <https://d2zs9tzlek599f.cloudfront.net/models/mrc/mrc_data.zip>`_
   * - :doc:`Word chunker <chunker>`
     - A word chunker model trained on CoNLL 2000 dataset
     - | `model <https://d2zs9tzlek599f.cloudfront.net/models/chunker/model.h5>`_
       | `params <https://d2zs9tzlek599f.cloudfront.net/models/chunker/model_info.dat.params>`_

References
----------

.. [#] Europarl-v7: A Parallel Corpus for Statistical Machine Translation, Philipp Koehn, MT Summit 2005
