# Training on a Google Cloud TPU instance

Welcome to the 🤗 Optimum-TPU training guide! This section covers how to fine-tune models using Google Cloud TPUs.

## Supported Models

See [Supported Models](../supported-architectures).

## Getting Started

### Prerequisites

Before starting the training process, ensure you have:

1. A configured Google Cloud TPU instance (see [Deployment Guide](../tutorials/tpu_setup))
2. Optimum-TPU installed with PyTorch/XLA support:
```bash
pip install optimum-tpu -f https://storage.googleapis.com/libtpu-releases/index.html
```

## Example Training Scripts

You can now follow one of our several example scripts to get started:
1. Gemma Fine-tuning:
   - See our [Gemma fine-tuning notebook](https://github.com/huggingface/optimum-tpu/blob/main/examples/language-modeling/gemma_tuning.ipynb) for a step-by-step guide

2. LLaMA Fine-tuning:
   - Check our [LLaMA fine-tuning notebook](https://github.com/huggingface/optimum-tpu/blob/main/examples/language-modeling/llama_tuning.ipynb) for detailed instructions