---
title: Examples
description: >-
  - Image Classification — Train an image classifier on the MNIST dataset -
  Transformer Language Model — A simple language model that learns to predict
  the...
canonical: 'https://lightning.ai/docs/fabric/stable/more/examples'
---
# Examples {#examples}

- [Image Classification](https://github.com/Lightning-AI/pytorch-lightning/blob/master/examples/fabric/image_classifier) — Train an image classifier on the MNIST dataset

- [Transformer Language Model](https://github.com/Lightning-AI/pytorch-lightning/blob/master/examples/fabric/language_model) — A simple language model that learns to predict the next word in a sentence

- [GAN](https://github.com/Lightning-AI/pytorch-lightning/blob/master/examples/fabric/dcgan) — Train a GAN that generates realistic human faces

- [Meta-Learning](https://github.com/Lightning-AI/pytorch-lightning/blob/master/examples/fabric/meta_learning) — Distributed training with the MAML algorithm on the Omniglot and MiniImagenet datasets

- [Large Language Models](https://github.com/Lightning-AI/litgpt/blob/main/tutorials/pretrain_tinyllama.md) — Pretrain a large language model (LLM)

- [Reinforcement Learning](https://github.com/Lightning-AI/pytorch-lightning/blob/master/examples/fabric/reinforcement_learning) — Implementation of the Proximal Policy Optimization (PPO) algorithm with multi-GPU support

- [K-Fold Cross Validation](https://github.com/Lightning-AI/lightning/tree/master/examples/fabric/kfold_cv) — Cross validation helps you estimate the generalization error of a model and select the best one.

- **Active Learning** — Coming soon

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- Parent: [More](/docs/fabric/2.6.6/more.md)