DOCUMENTATION

Install the Fleet SDK and run your first training job in minutes.

How Fleet authenticates your SDK and CLI requests.

Fine-tune models on your dataset. Methods, hyperparameters, and hardware tiers.

How Fleet tracks, bills, and manages storage for models, datasets, and checkpoints.

Balance, transactions, storage costs, and auto-recharge.

A tour of the Fleet dashboard and what each section does.

Upload base models, fine-tune them, and manage outputs and checkpoints from the dashboard.

Upload and manage the training datasets used by your fine-tuning jobs.

Track training jobs, stream live logs, watch metrics, and cancel runs.

Spin up inference endpoints, test them live, and manage their lifecycle.

Complete reference for the Fleet Python SDK.

The Fleet command-line interface. Manage models, jobs, datasets, and deployments from your terminal.