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Compression
===========
The following tutorials will help you learn how to use compression techniques with MXNet.

.. container:: cards

   .. card::
      :title: Compression: float16
      :link: https://mxnet.apache.org/api/faq/float16

      How to use float16 in your model to boost training speed.

   .. card::
      :title: Gradient Compression
      :link: https://mxnet.apache.org/api/faq/gradient_compression

      How to use gradient compression to reduce communication bandwidth and increase speed.

   .. card::
      :title: Inference with Quantized Models
      :link: https://gluon-cv.mxnet.io/build/examples_deployment/int8_inference.html

      How to use quantized GluonCV models for inference on Intel Xeon Processors to gain higher performance.

   .. card::
      :title: Compression: int8
      :link: int8.html

      How to use int8 in your model to boost training speed.


.. toctree::
   :hidden:
   :glob:

   *
   Float16 <https://mxnet.apache.org/api/faq/float16>
   Gradient Compression  <https://mxnet.apache.org/api/faq/gradient_compression>
   GluonCV with Quantized Models <https://gluon-cv.mxnet.io/build/examples_deployment/int8_inference.html>