Farama-Foundation/Minari

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

1772 stars · 81 forks observed · 2026-10-14

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Minari is a Python library providing a standard format for offline reinforcement learning datasets, with popular reference datasets and utilities for creating, storing, and loading them. It integrates with Gymnasium and offers a CLI for browsing and downloading datasets like D4RL.

Use cases

• download offline RL datasets like D4RL
• create offline RL datasets by collecting trajectories from Gymnasium environments
• load and iterate over offline RL episodes for training
• run behavioral cloning or implicit Q-learning experiments
• share offline RL datasets in a standard format

When to choose

• you need offline RL datasets in a standard format compatible with Gymnasium
• you want to collect your own trajectory datasets from Gymnasium environments
• you want access to reference datasets like D4RL, Minigrid, or PointMaze

When to avoid

• you need online reinforcement learning environments rather than offline datasets
• you work outside Python or need non-Gymnasium data formats

Facets

library · maturity active

machine-learning reinforcement-learning cli serialization reinforcement-learning machine-learning artificial-intelligence python cli cross-platform offline-rl gymnasium d4rl datasets farama dataset

Member repositories

For agents

markdown · JSON · MCP: product_card(name="Farama-Foundation/Minari")