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Jethro Kuan c7e349e73d
docs: default_root_path -> default_root_dir (#4942) 
* docs: default_root_path -> default_root_dir

* Apply suggestions from code review

* fix

Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>

* update notebook

Co-authored-by: Jethro Kuan <jethro.kuan@bytedance.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>
Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com>
 		2020-12-02 19:17:34 -05:00
..
01-mnist-hello-world.ipynb add congratulations at the end of our notebooks (#4555) 2020-11-07 12:05:29 +00:00
02-datamodules.ipynb add congratulations at the end of our notebooks (#4555) 2020-11-07 12:05:29 +00:00
03-basic-gan.ipynb add congratulations at the end of our notebooks (#4555) 2020-11-07 12:05:29 +00:00
04-transformers-text-classification.ipynb add congratulations at the end of our notebooks (#4555) 2020-11-07 12:05:29 +00:00
05-trainer-flags-overview.ipynb docs: default_root_path -> default_root_dir (#4942) 2020-12-02 19:17:34 -05:00
README.md Fix broken trainer flags nb (#4159) 2020-10-15 23:04:54 +02:00

README.md

Lightning Notebooks ⚡

Official Notebooks

You can easily run any of the official notebooks by clicking the 'Open in Colab' links in the table below 😄

Notebook Description Colab Link
MNIST Hello World Train your first Lightning Module on the classic MNIST Handwritten Digits Dataset. Open In Colab
Datamodules Learn about DataModules and train a dataset-agnostic model on MNIST and CIFAR10. Open In Colab
GAN Train a GAN on the MNIST Dataset. Learn how to use multiple optimizers in Lightning. Open In Colab
BERT Fine-tune HuggingFace Transformers models on the GLUE Benchmark Open In Colab
Trainer Flags Overview of the available Lightning Trainer flags Open In Colab