Running a Task | Transformer Lab

📄️ Quick Start

This quick start helps a new Teams user go from login to running their first task.

📄️ Task Submission Overview

This page explains how tasks work in Transformer Lab and how the different pieces fit together. It links out to focused guides for the GUI, CLI, and advanced task configurations.

📄️ Task Submission Using the GUI

This guide shows how to submit tasks from the Transformer Lab user interface, using the same building blocks you see in the app:

📄️ Task Submission Using the CLI

Transformer Lab provides a CLI called lab for managing tasks and jobs from the terminal.

This guide explains how to define and configure task parameters in Transformer Lab. Parameters are used to pass configuration values, hyperparameters, and other settings to your task scripts, which can be accessed via lab.get_config().

📄️ Sweeps

Once you are comfortable running single tasks, you can take advantage of parameterization and sweeps to explore many configurations automatically.

📄️ Using Existing Training Scripts Inside Tasks

If your tasks already launch your own training or evaluation scripts (via the run: command in task.yaml), you do not need to rewrite those scripts for Transformer Lab.

📄️ Creating Tasks From Scratch

This guide explains how to create a task from scratch, how task files appear on the compute machine, and how to modify your training scripts so that important outputs are available later in the GUI.

📄️ Task YAML Structure

This guide explains how to format YAML files for creating tasks in Transformer Lab. Tasks define jobs that run on compute providers and can include training scripts, evaluation scripts, or any other computational workloads.