Weights & Biases: The AI Developer Platform

Weights & Biases is the machine learning platform for developers to build better models faster. Use W&B's lightweight, interoperable tools to quickly track experiments, version and iterate on datasets, evaluate model performance, reproduce models, visualize results and spot regressions, and share findings with colleagues.

Weights & Biases: The AI Developer Platform

Published on: April 15, 2024
Last updated: January 05, 2026 Read in fullscreen view

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What is W&B?

Weights & Biases (W&B) is the AI developer platform, with tools for training models, fine-tuning models, and leveraging foundation models.

Set up W&B in 5 minutes, then quickly iterate on your machine learning pipeline with the confidence that your models and data are tracked and versioned in a reliable system of record.

This diagram outlines the relationship between W&B products.

W&B Models is a set of lightweight, interoperable tools for machine learning practitioners training and fine-tuning models.

Experiments: Machine learning experiment tracking
Model Registry: Manage production models centrally
Launch: Scale and automate workloads
Sweeps: Hyperparameter tuning and model optimization

W&B Prompts is for debugging and evaluating LLMs.

W&B Core is a core set of powerful building blocks for tracking and visualizing data and models, and communicating results.

Artifacts: Version assets and track lineage
Tables: Visualize and query tabular data
Reports: Document and collaborate on your discoveries

Are you a first-time user of W&B?

Start exploring W&B with these resources:

Intro Notebook: Run quick sample code to track experiments in 5 minutes
Quickstart: Read a quick overview of how and where to add W&B to your code
Explore our Integrations guide and our W&B Easy Integration YouTube playlist for information on how to integrate W&B with your preferred machine learning framework.
View the API Reference guide for technical specifications about the W&B Python Library, CLI, and Query Language operations.

How does W&B work?

We recommend you read the following sections in this order if you are a first-time user of W&B:

Learn about Runs, W&B's basic unit of computation.
Create and track machine learning experiments with Experiments.
Discover W&B's flexible and lightweight building block for dataset and model versioning with Artifacts.
Automate hyperparameter search and explore the space of possible models with Sweeps.
Manage the model lifecycle from training to production with Model Management.
Visualize predictions across model versions with our Data Visualization guide.
Organize W&B Runs, embed and automate visualizations, describe your findings, and share updates with collaborators with Reports.

Final Words

Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production machine learning models. Get started with W&B today, sign up for a free account!

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