wandb

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The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

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Python MITCreated Mar 24, 2017

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Maintenance: Very active (0d since push); As of today · Source: github_public_v1
Provenance: Not a fork · Organization account; As of today · Source: github_public_v1
Security (OSV): No lockfile; As of today · Source: none

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Overview

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Capability facts

CLI: CLI entrypoint
Source: pyproject.toml:[project.scripts] · Jul 11, 2026
Languages: python
Source: github.language+pyproject.toml · Jul 11, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Jul 11, 2026)

pip install wandb

Source link

README

Install the wandb library

pip install wandb

W&B Hosting Options

Weights & Biases is available in the cloud or installed on your private infrastructure. Set up a W&B Server in a production environment in one of three ways:

Multi-tenant Cloud: Fully managed platform deployed in W&B’s Google Cloud Platform (GCP) account in GCP’s North America regions.
Dedicated Cloud: Single-tenant, fully managed platform deployed in W&B’s AWS, GCP, or Azure cloud accounts. Each Dedicated Cloud instance has its own isolated network, compute and storage from other W&B Dedicated Cloud instances.
Self-Managed: Deploy W&B Server on your AWS, GCP, or Azure cloud account or within your on-premises infrastructure.

See the Hosting documentation in the W&B Developer Guide for more information.