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volotat/mini-AGI

Continual learning model trained from scratch on 8GB VRAM laptop with batch-1 stream of data.

Visit GitHub
Python
1.3k
205
1 contributors
MIT License
AchievementsView all →
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Momentum

How fast volotat/mini-AGI is gaining stars, and where it lands on Trendshift and GitHub Trending

Activity and trending

Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending

Sep 20 – Oct 23, 2026

Stars +1,251 in 34 days

0100200300
294

Forks +205 in 34 days

0204060
47

Merged PRs 0 in 34 days

01

Trendshift Trendingwhere the repository ranked each day it made the top 25

Top 25 in Python

22
Sep 20Sep 25Sep 30Oct 5Oct 10Oct 15Oct 20
The left and right arrow keys step from day to day; Home and End go to the first and the last

Stars, forks, merged pull requests and Trendshift Trending rank, by day
DayStars gainedForks gainedMerged PRsPython
Sun, Sep 20, 2026+0+00Not trending
Mon, Sep 21, 2026+294+220Not trending
Tue, Sep 22, 2026+291+470#22
Wed, Sep 23, 2026+124+350Not trending
Thu, Sep 24, 2026+36+60Not trending
Fri, Sep 25, 2026+15+10Not trending
Sat, Sep 26, 2026+8+30Not trending
Sun, Sep 27, 2026+8+20Not trending
Mon, Sep 28, 2026+7+00Not trending
Tue, Sep 29, 2026+12+10Not trending
Wed, Sep 30, 2026+61+80Not trending
Thu, Oct 1, 2026+149+270Not trending
Fri, Oct 2, 2026+61+140Not trending
Sat, Oct 3, 2026+46+80Not trending
Sun, Oct 4, 2026+53+120Not trending
Mon, Oct 5, 2026+17+60Not trending
Tue, Oct 6, 2026+12+30Not trending
Wed, Oct 7, 2026+8+20Not trending
Thu, Oct 8, 2026+7+00Not trending
Fri, Oct 9, 2026+6+40Not trending
Sat, Oct 10, 2026+8+10Not trending
Sun, Oct 11, 2026+3+10Not trending
Mon, Oct 12, 2026+2+00Not trending
Tue, Oct 13, 2026+1+00Not trending
Wed, Oct 14, 2026+0+00Not trending
Thu, Oct 15, 2026+3+10Not trending
Fri, Oct 16, 2026+4+00Not trending
Sat, Oct 17, 2026+4+00Not trending
Sun, Oct 18, 2026+7+10Not trending
Mon, Oct 19, 2026+1+00Not trending
Tue, Oct 20, 2026+0+00Not trending
Wed, Oct 21, 2026+2+00Not trending
Thu, Oct 22, 2026+1+00Not trending
Fri, Oct 23, 2026+0+00Not trending
Total+1,251+2050
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Mentions and achievements

Where people are talking about volotat/mini-AGI, and every badge it has earned
  1. Oct 71 post

    • 8GB 显存，从零训 11 亿参数，读什么学什么。 volotat/mini-AGI，19 天 1209★，MIT 开源。 权重存硬盘按需上卡，参数量只看硬盘；读 100 万字新领域，旧的只丢 3%。 还是玩具级、权重没放完，但这条路在消费级硬件上成立了。 #本地大模型 #持续学习 #miniAGI

      Read full on X, posted by @ataosky

      @ataosky · x.com

  2. 13 days earlier
  3. Sep 241 post

    • 模型边读边学，怎么避免新内容把旧知识挤走？mini-AGI 的实验给了个反直觉的线索。 它在 8GB 显存上从零训练，把专家权重和优化器状态放在磁盘，按需换入显存。但在单主题连续学习实验中，压住遗忘的关键不是专家切换，而是把主干学习率降到专家的十分之一。模型目前还是玩具级，值得看的是这个实现取舍。

      Read full on X, posted by @vintcessun

      @vintcessun · x.com

  4. Sep 231 post

    • AGI FUTURE. ALL HUMANS WILL LIVE LIKE THIS

      Read full on X, posted by @AiEconomyY3000

      @AiEconomyY3000 · x.com

  5. Sep 222 posts4 posts

    • mini-AGI: Continual-learning dynamically looped transformer with evolutionary growth (on a laptop)

      Read full on Reddit

      r/LocalLLM

    • mini-AGI: Continual-learning dynamically looped transformer with evolutionary growth (on a laptop)

      Read full on Reddit

      r/deeplearning

    • mini-AGI: Continual-learning dynamically looped transformer with evolutionary grown (on a laptop)

      Read full on Reddit

      r/LocalLLaMA

    • A GitHub repo promises a model that keeps learning after training ends. It does it on an 8GB laptop GPU, one sample at a time. Mini-AGI is a continual learning model trained from scratch. No cloud,…

      Read full on X, posted by @ToolDeckAI

      @ToolDeckAI · x.com

  6. Sep 213 posts

    • Kev: Tiny Jev-like family of decision models built on top of Qwen3.5 (

      Read full on X, posted by @betterhn50

      @betterhn50 · x.com

    • Show HN: Mini-AGI – Dynamic continual learning model trained on 8GB VRAM

      Read full on Reddit

      r/hackernews

    • Show HN: Mini-AGI – Dynamic continual learning model trained on 8GB VRAM

      Read full on Reddit

      r/hypeurls

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