Getting Started

TT-NN is a user-friendly API for running ML workloads on Tenstorrent hardware.

The GitHub repository for the project is located here: https://github.com/tenstorrent/tt-metal

Installation and environment setup instructions are in the installation guide.

1. Install and Build

Install and build the project by following the instructions in the installation guide.

2. Explore Our Model Demos

Get started with the model of your choice. Install one of numerous configurations. See the model demo list for details.

3. TT-NN Tutorial: Multi-Head Attention (Simple)

Learn the basics of multi-head attention operations with TT-NN with a simple example: TT-NN simple module.

4. TT-NN Tutorial: Multi-Head Attention (Optimized)

Dive deeper into multi-head attention operations in TT-NN, optimizing performance: optimizing performance.

Where To Go From Here

Take a look at more code examples for TT-NN or the other tutorials on using TT-NN with Jupyter Notebooks.

If you’re an internal TT-NN developer, please read and review the contribution standards.