From 03aa142adc97664cd3d23af2c7e1f6bdde2dc174 Mon Sep 17 00:00:00 2001 From: William Falcon Date: Fri, 28 Jun 2019 14:12:34 -0400 Subject: [PATCH] changed read me --- README.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index bb9df123ea..7b5251b890 100644 --- a/README.md +++ b/README.md @@ -27,7 +27,9 @@ Keras and fast.ai are too abstract for researchers. Lightning abstracts the full ## Why do I want to use lightning? -Because you want to use best practices and get gpu training, multi-node training, checkpointing, mixed-precision, etc... for free, but still want granular control of the meat of the training, validation and testing loops. +Because you don't want to define a training loop, validation loop, gradient clipping, checkpointing, loading, +gpu training, etc... every time you start a project. Let lightning handle all of that for you and you just define your +data and what happens in the training, testing and validation loop To use lightning do 2 things: 1. [Define a Trainer](https://github.com/williamFalcon/pytorch-lightning/blob/master/examples/new_project_templates/trainer_cpu_template.py).