In this Quick Start tutorial, we’ll be training Qwen 2.5 14B to play 2048, a simple game that requires forward planning and basic math skills.
Reading time: 15 minTraining time: 2 hoursTotal cost: Free!
Step 1: Provision W&B API key
ART is an open source library and works across infra and observability providers. To keep things simple in this tutorial, we’ll exclusively use Weights & Biases services, which means we’ll only need to provision one API key. We’ll use these services:
- W&B Training - autoscale GPUs for inference and training
- W&B Models - record metrics like reward
- W&B Weave - record your model’s traces as it generates completions
- W&B Artifacts - store and manage your model’s checkpoints
Weights & Biases currently provides a small free tier for all the services we’ll use during this quickstart, so you shouldn’t need to add a credit card to get started.
Once you have your Weights & Biases API key, open the notebook in Google Colab and set it in the Environment Variables cell. Then continue on to the next step.
Step 2: Run the notebook
At the top of the notebook you should see a small Run all button. Press it to begin training your model.
Step 3: Track metrics
While your run progresses, observe its traces and metrics in your W&B workspace. You should start seeing some progress in the first 20-30 steps. If you have questions along the way, please ask in the Discord. Happy training! 
