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Liquid4All/ifstruct

#LLM evaluation
Visit GitHub
Python
50
9
3 contributors
Apache License 2.0
FeaturedAdvertise to 180K+ monthly visitors
Bifrost

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Momentum

How fast Liquid4All/ifstruct 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 4 – Oct 27, 2026

Stars +9 in 54 days

012
2

Forks +2 in 54 days

01
1

Merged PRs 1 in 54 days

01
1

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

Not in the Trendshift top 25 in this period

Sep 4Sep 11Sep 18Sep 25Oct 2Oct 9Oct 16Oct 23
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 PRs
Fri, Sep 4, 2026+2+00
Sat, Sep 5, 2026+1+10
Sun, Sep 6, 2026+1+00
Mon, Sep 7, 2026+1+00
Tue, Sep 8, 2026+0+00
Wed, Sep 9, 2026+0+00
Thu, Sep 10, 2026+0+00
Fri, Sep 11, 2026+0+00
Sat, Sep 12, 2026+0+00
Sun, Sep 13, 2026+0+00
Mon, Sep 14, 2026+0+00
Tue, Sep 15, 2026+0+00
Wed, Sep 16, 2026+1+00
Thu, Sep 17, 2026+1+00
Fri, Sep 18, 2026+0+00
Sat, Sep 19, 2026+0+10
Sun, Sep 20, 2026+0+00
Mon, Sep 21, 2026+0+00
Tue, Sep 22, 2026+0+00
Wed, Sep 23, 2026+0+00
Thu, Sep 24, 2026+0+00
Fri, Sep 25, 2026+0+00
Sat, Sep 26, 2026+0+00
Sun, Sep 27, 2026+0+00
Mon, Sep 28, 2026+0+00
Tue, Sep 29, 2026+0+00
Wed, Sep 30, 2026+0+00
Thu, Oct 1, 2026+0+00
Fri, Oct 2, 2026+0+00
Sat, Oct 3, 2026+0+00
Sun, Oct 4, 2026+0+00
Mon, Oct 5, 2026+0+00
Tue, Oct 6, 2026+0+00
Wed, Oct 7, 2026+1+00
Thu, Oct 8, 2026+0+00
Fri, Oct 9, 2026+0+00
Sat, Oct 10, 2026+0+00
Sun, Oct 11, 2026+0+00
Mon, Oct 12, 2026+0+00
Tue, Oct 13, 2026+0+00
Wed, Oct 14, 2026+0+00
Thu, Oct 15, 2026+0+00
Fri, Oct 16, 2026+0+00
Sat, Oct 17, 2026+1+00
Sun, Oct 18, 2026+0+01
Mon, Oct 19, 2026+0+00
Tue, Oct 20, 2026+0+00
Wed, Oct 21, 2026+0+00
Thu, Oct 22, 2026+0+00
Fri, Oct 23, 2026+0+00
Sat, Oct 24, 2026+0+00
Sun, Oct 25, 2026+0+00
Mon, Oct 26, 2026+0+00
Tue, Oct 27, 2026+0+00
Total+9+21
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. Jun 302 posts

    • The results: LFM2.5-350M (base): 21.10% LFM2.5-350M (+ RL): 44.90% Qwen3.5-4B: 36.25% granite-4.0-h-tiny: 38.75% After RL training on a held-out set, the 350M model beats models 10x its size.

      Read full on X, posted by @helloiamleonie

      @helloiamleonie · x.com

    • LFM2.5-350M starts at 21.10% and reaches 44.90% after training, ahead of Qwen3.5-4B at 36.25% and granite-4.0-h-tiny at 38.75%. Frontier models near 100%. (4/n)

      Read full on X, posted by @liquidai

      @liquidai · x.com

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