# ytongbai/LVM

Repository: https://github.com/ytongbai/LVM
Canonical: https://ross.abutalabs.com/products/lvm
Language: Python
License: Apache-2.0
License Family: permissive
Last push: 2024-06-28T04:44:40+00:00

## Health v2 (maintenance only)
Score: 30/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 0, release rhythm 35, longevity 89
- inputs: {"age_days": 1247, "days_push": 796, "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 1838, forks 61 (observed 2026-08-28T04:05:42.842872+00:00)

## What it is
LVM is a large vision model trained with sequential next-token prediction over 'visual sentences', using no linguistic data. It builds on OpenLLaMA for autoregressive modeling and OpenMuse VQGAN for image tokenization, with training code and model definitions from 100M to 30B parameters.

## Use cases
- train a large vision model without language data
- pretrain autoregressive models on visual tokens
- run next-token prediction over images and videos
- solve vision tasks with visual prompts
- scale vision model training across model sizes
- convert images into visual tokens with VQGAN

## When to choose
- you want to pretrain or fine-tune large vision-only autoregressive models
- you need JAX-based distributed training on GPU or TPU clusters
- you are researching language-free visual representation learning

## When to avoid
- you need a ready-made inference API or hosted model for production apps
- you want off-the-shelf image classification or detection rather than research training
- you lack multi-GPU/TPU resources for large-scale training

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning, llm-training
- domain: machine-learning, deep-learning, computer-vision, artificial-intelligence
- platform: python
- tags: vision-model, autoregressive, visual-sentences, vqgan, pretraining, jax, research, gpu, linux

## Member repositories
- ytongbai/LVM (main) score 30

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:42.842872+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 2026-08-30T03:18:17.653393+00:00, confidence not recorded.
  - readme: https://github.com/ytongbai/LVM (fetched 2026-08-28T04:05:42.842872+00:00, sha f682bfd120ce)
- Data as of 2026-08-30T08:39:29.467469+00:00.