# AlmondGod/tinyworlds

A minimal implementation of DeepMind's Genie world model

Repository: https://github.com/AlmondGod/tinyworlds
Canonical: https://ross.abutalabs.com/products/tinyworlds
Homepage: https://x.com/Almondgodd/status/1971314283184259336
Language: Python
License: MIT
License Family: permissive
Last push: 2026-04-15T20:18:29+00:00

## Health v2 (maintenance only)
Score: 54/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 77, release rhythm 35, longevity 34
- inputs: {"age_days": 479, "days_push": 140, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1378, forks 104 (observed 2026-08-28T04:04:33.568611+00:00)

## What it is
A minimal Python implementation of DeepMind's Genie autoregressive world model, including a video tokenizer, action tokenizer, and dynamics model. It is designed as an educational resource for understanding unsupervised, action-less video world modeling.

## Use cases
- understand how DeepMind's Genie world model works
- train an autoregressive world model on game video frames
- learn latent action inference without action labels
- experiment with space-time transformers and FSQ tokenizers
- generate playable video predictions from pretrained checkpoints

## When to choose
- you want a small, readable codebase to learn Genie-style world models
- you want to train or fine-tune a world model on your own video datasets
- you need a reference implementation of latent action modeling

## When to avoid
- you need a production-grade, scalable video generation system like VEO
- you want a polished application with a UI rather than research code
- you lack GPU resources for training transformer models

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, llm-training
- domain: machine-learning, deep-learning, artificial-intelligence
- platform: python
- tags: world-model, genie, video-generation, transformer, research, educational, gpu

## Member repositories
- AlmondGod/tinyworlds (main) score 54

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:33.568611+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:40:20.406505+00:00, confidence not recorded.
  - readme: https://github.com/AlmondGod/tinyworlds (fetched 2026-08-28T04:04:33.568611+00:00, sha 508a76bb9161)
- Data as of 2026-08-30T08:39:29.467469+00:00.