Weightslab DocumentationΒΆ

Weightslab is a Python SDK to inspect, monitor, and edit training behavior for computer vision workflows.

Inspect, edit, and optimize model training with a unified workflow.

πŸš€ Quickstart

Install, build, and run Weightslab documentation locally in minutes.

Quickstart
🧭 Four-Way Approach

Understand how model, data, hyperparameters, and logger workflows connect.

Four-Way SDK Approach
🧠 Model + Data Control

Learn how to wrap training components and iterate on difficult samples.

Model Interaction
πŸ“š User Functions

Reference all public SDK functions with usage-oriented explanations.

User Functions Reference
πŸ§ͺ Use-Case Example

Follow a complete MNIST integration with comments and practical rationale.

Use Case Example (PyTorch)
⚑ PyTorch Lightning

Integrate Weightslab with Lightning, including multi-GPU configuration.

PyTorch Lightning Integration
πŸ–₯️ Weights Studio

Deploy and operate the UI: architecture, Docker, ports, and actions.

Weights Studio Guide

Weightslab in one sentence

Wrap your training script once, then monitor, tag/discard, adjust, and improve continuously.