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5 changes: 4 additions & 1 deletion advanced_source/cpp_export.rst
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Loading a PyTorch model in C++
Loading a PyTorch Model in C++
==============================

This tutorial requires PyTorch 1.0 (preview) or later. For installation information
visit http://pytorch.org/get-started.

As its name suggests, the primary interface to PyTorch is the Python
programming language. While Python is a suitable and preferred language for
many scenarios requiring dynamism and ease of iteration, there are equally many
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3 changes: 3 additions & 0 deletions beginner_source/chatbot_tutorial.py
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######################################################################
# This example requires PyTorch 1.0 (preview) or later.
# For installation information visit http://pytorch.org/get-started.
#
# In this tutorial, we explore a fun and interesting use-case of recurrent
# sequence-to-sequence models. We will train a simple chatbot using movie
# scripts from the `Cornell Movie-Dialogs
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12 changes: 6 additions & 6 deletions beginner_source/deploy_seq2seq_hybrid_frontend_tutorial.py
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######################################################################
# This example requires PyTorch 1.0 (preview) or later. For installation
# information visit http://pytorch.org/get-started.
#
# This tutorial will walk through the process of transitioning a
# sequence-to-sequence model to Torch Script using PyTorch’s Hybrid
# Frontend. The model that we will convert is the chatbot model from the
# `Chatbot tutorial <>`__. While the `introductory hybrid frontend
# tutorials <>`__ are useful for gaining an understanding of the
# work-flow, purpose, and basic syntax of the feature, this document
# covers a more challenging model and a more practical use-case. You can
# either treat this tutorial as a “Part 2” to the `Chatbot tutorial <>`__
# `Chatbot tutorial <https://pytorch.org/tutorials/beginner/chatbot_tutorial.html>`__.
# You can either treat this tutorial as a “Part 2” to the Chatbot tutorial
# and deploy your own pretrained model, or you can start with this
# document and use a pretrained model that we host. In the latter case,
# you can reference the original `Chatbot tutorial <>`__ for details
# you can reference the original Chatbot tutorial for details
# regarding data preprocessing, model theory and definition, and model
# training.
#
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===============================================
**Author:** `Nathan Inkawhich <https://github.com/inkawhich>`_

This tutorial requires PyTorch 1.0 (preview) or later. For installation
information visit http://pytorch.org/get-started.

This document is meant to highlight the syntax of the Hybrid Frontend
through a non-code intensive example. The Hybrid Frontend is one of the
new shiny features of Pytorch 1.0 and provides an avenue for developers
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6 changes: 3 additions & 3 deletions index.rst
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:description: :doc:`beginner/transfer_learning_tutorial`

.. customgalleryitem::
:figure: /_static/img/hybrid_frontend/220px-KnnClassification.png
:figure: /_static/img/hybrid.png
:tooltip: Experiment with some of the key features of the PyTorch hybrid frontend
:description: :doc:`beginner/hybrid_frontend_tutorial`
:description: :doc:`beginner/deploy_seq2seq_hybrid_frontend_tutorial`

.. customgalleryitem::
:figure: /_static/img/thumbnails/floppy.png
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beginner/data_loading_tutorial
beginner/pytorch_with_examples
beginner/transfer_learning_tutorial
beginner/hybrid_frontend_tutorial
beginner/deploy_seq2seq_hybrid_frontend_tutorial
beginner/saving_loading_models

.. toctree::
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