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.. S3PRL documentation master file, created by
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S3PRL
=====
.. image:: https://raw.githubusercontent.com/s3prl/s3prl/master/file/S3PRL-logo.png
**S3PRL** is a toolkit targeting for Self-Supervised Learning for speech processing.
Its full name is **S**\elf-**S**\upervised **S**\peech **P**\re-training and **R**\epresentation **L**\earning.
It supports the following three major features:
* **Pre-training**
* You can train the following models from scratch:
* *Mockingjay*, *Audio ALBERT*, *TERA*, *APC*, *VQ-APC*, *NPC*, and *DistilHuBERT*
* **Pre-trained models (Upstream) collection**
* Easily load most of the existing upstream models with pretrained weights in a unified I/O interface.
* Pretrained models are registered through torch.hub, which means you can use these models in your own project by one-line plug-and-play without depending on this toolkit's coding style.
* **Downstream Evaluation**
* Utilize upstream models in lots of downstream tasks
* The official implementation of the `SUPERB Benchmark <https://superbbenchmark.org/>`_
Getting Started
---------------
.. toctree::
:caption: Getting started
./tutorial/installation.rst
./tutorial/upstream_collection.rst
./tutorial/problem.rst
How to Contribute
-----------------
.. toctree::
:caption: How to Contribute
./contribute/general.rst
./contribute/upstream.rst
API Documentation
-----------------
.. autosummary::
:caption: API Documentation
:toctree: _autosummary
:template: custom-module-template.rst
:recursive:
s3prl.nn
s3prl.problem
s3prl.task
s3prl.dataio
s3prl.metric
s3prl.util
Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`