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60 lines
1.6 KiB
ReStructuredText
60 lines
1.6 KiB
ReStructuredText
.. image:: https://badge.fury.io/py/labml-nn.svg
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:target: https://badge.fury.io/py/labml-nn
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.. image:: https://pepy.tech/badge/labml-nn
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:target: https://pepy.tech/project/labml-nn
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`LabML Neural Networks <http://lab-ml.com/labml_nn/index.html>`_
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================================================================
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This is a collection of simple PyTorch implementation of various neural network architectures and layers. We will keep adding to this.
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Transformers
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------------
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`Transformers module <http://lab-ml.com/labml_nn/transformers>`_ contains implementations for
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`multi-headed attention <http://lab-ml.com/labml_nn/transformers/mha.html>`_
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and
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`relative multi-headed attention <http://lab-ml.com/labml_nn/transformers/relative_mha.html>`_.
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✅ TODO
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-------
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* Recurrent Highway Networks
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* LSTMs
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Please create a Github issue if there's something you'ld like to see implemented here.
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Installation
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------------
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.. code-block:: console
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pip install labml_nn
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Links
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-----
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`💬 Slack workspace for discussions <https://join.slack.com/t/labforml/shared_invite/zt-egj9zvq9-Dl3hhZqobexgT7aVKnD14g/>`_
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`📗 Documentation <http://lab-ml.com/>`_
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`📑 Articles & Tutorials <https://medium.com/@labml/>`_
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`👨🏫 Samples <https://github.com/lab-ml/samples>`_
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Citing LabML
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------------
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If you use LabML for academic research, please cite the library using the following BibTeX entry.
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.. code-block:: bibtex
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@misc{labml,
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author = {Varuna Jayasiri, Nipun Wijerathne},
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title = {LabML: A library to organize machine learning experiments},
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year = {2020},
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url = {https://lab-ml.com/},
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}
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