From f4030a7cf8dd304c1eec94b10041e2dff44efc99 Mon Sep 17 00:00:00 2001 From: William Falcon Date: Thu, 27 Jun 2019 14:45:54 -0400 Subject: [PATCH] changed read me --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 0b3461dae4..cd9a25e878 100644 --- a/README.md +++ b/README.md @@ -30,7 +30,7 @@ Keras and fast.ai are too abstract for researchers. Lightning abstracts the full 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. 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) (which will run ALL your models). +1. [Define a Trainer](https://github.com/williamFalcon/pytorch-lightning/blob/master/examples/new_project_templates/trainer_cpu_template.py). 2. [Define a LightningModel](https://github.com/williamFalcon/pytorch-lightning/blob/master/examples/new_project_templates/lightning_module_template.py). ## What does lightning control for me?