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Get started with distil labs

distil labs is a developer platform where engineers train and deploy small models that match frontier accuracy at 80% lower cost.

Start with a coding agent

Section titled “Start with a coding agent”
claude "Let's get started with distillabs.ai/onboarding.md"

Runs in your terminal.

Your agent installs the CLI, creates your account, and trains your first model with you. It stops for your go-ahead at four points, so nothing runs that you have not seen. The whole flow takes 30 to 45 minutes, and jobs run for 20 to 35 of those minutes.

Start with the CLI

Section titled “Start with the CLI”
curl -fsSL https://cli-assets.distillabs.ai/install.sh | sh
distil signup

distil signup opens your browser and hands the session back, so you finish signed in. If you already have an account, run distil auth instead. You can also sign up at app.distillabs.ai/sign-up.

Then train and deploy a model with five commands. The build overview covers each one:

distil seed-dataset create --data ./my-data-dir
# Seed dataset created with ID: <seed-dataset-id>

distil training-dataset create-from-seed-dataset <seed-dataset-id>
# Training dataset created with ID: <training-dataset-id>

distil slm create-from-training-dataset <training-dataset-id>
# SLM created with ID: <slm-id>

distil deployment create-from-slm <slm-id>
distil deployment endpoint <deployment-id>     # URL and API key

Your trained model is ready for hosted inference, or you can run it locally.

Next steps

Section titled “Next steps”