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* Created using Colaboratory
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Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com>
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* Apply suggestions from code review
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
Co-authored-by: Jirka Borovec <Borda@users.noreply.github.com>
Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com>
Co-authored-by: edenlightning <66261195+edenlightning@users.noreply.github.com>
Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
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| .. | ||
| 01-mnist-hello-world.ipynb | ||
| 02-datamodules.ipynb | ||
| 03-basic-gan.ipynb | ||
| 04-transformers-text-classification.ipynb | ||
| 05-trainer-flags-overview.ipynb | ||
| README.md | ||
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. |  |
| Datamodules | Learn about DataModules and train a dataset-agnostic model on MNIST and CIFAR10. | |
| GAN | Train a GAN on the MNIST Dataset. Learn how to use multiple optimizers in Lightning. | |
| BERT | Fine-tune HuggingFace Transformers models on the GLUE Benchmark | |
| Trainer Flags | Overview of the available Lightning Trainer flags |
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