From 2ad9a9708b430571c7faaf51cac72313012b00d6 Mon Sep 17 00:00:00 2001 From: William Falcon Date: Fri, 23 Aug 2019 16:10:45 -0400 Subject: [PATCH] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index cbb2a393..37cd6366 100644 --- a/README.md +++ b/README.md @@ -36,7 +36,7 @@ pip install pytorch-lightning Lightning is a very lightweight wrapper on PyTorch. This means you don't have to learn a new library. To use Lightning, simply refactor your research code into the [LightningModule](https://github.com/williamFalcon/pytorch-lightning#how-do-i-do-use-it) format and Lightning will automate the rest. Lightning guarantees tested, correct, modern best practices for the automated parts. ## Starting a new project? -[Use our seed aimed at reproducibility!](https://github.com/williamFalcon/pytorch-lightning-conference-seed) +[Use our seed-project aimed at reproducibility!](https://github.com/williamFalcon/pytorch-lightning-conference-seed) ## Why do I want to use lightning? Every research project starts the same, a model, a training loop, validation loop, etc. As your research advances, you're likely to need distributed training, 16-bit precision, checkpointing, gradient accumulation, etc.