# Lightning Notebooks ⚡

## Official Notebooks

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

| Notebook | Description | Colab Link |
| :--- | :--- | :---: |
| __MNIST Hello World__   | Train your first Lightning Module on the classic MNIST Handwritten Digits Dataset. | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/PytorchLightning/pytorch-lightning/blob/master/notebooks/01_mnist_hello_world.ipynb) |
| __Datamodules__     | Learn about DataModules and train a dataset-agnostic model on MNIST and CIFAR10.| [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/PytorchLightning/pytorch-lightning/blob/master/notebooks/02_datamodules.ipynb)|
| __GAN__     | Train a GAN on the MNIST Dataset. Learn how to use multiple optimizers in Lightning.   | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/PytorchLightning/pytorch-lightning/blob/master/notebooks/03_basic_gan.ipynb) |
| __BERT__     | Fine-tune HuggingFace Transformers models on the GLUE Benchmark | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/PytorchLightning/pytorch-lightning/blob/master/notebooks/04_transformers_text_classification.ipynb) |