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bespokelabsai/nimble

Local typed decisions, contrastive data curation, and model evaluation.

Visit GitHub
Python
2.3k
180
2 contributors
AchievementsView all →
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Momentum

How fast bespokelabsai/nimble 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 18 – Nov 5, 2026

Stars +2,062 in 49 days

05001K
671

Forks +180 in 49 days

0204060
46

Merged PRs 16 in 49 days

024
4

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

Top 25 overall

9

Top 25 in Python

414
Sep 18Sep 25Oct 2Oct 9Oct 16Oct 23Oct 30
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 PRsAll languagesPython
Fri, Sep 18, 2026+0+60Not trendingNot trending
Sat, Sep 19, 2026+193+271Not trendingNot trending
Sun, Sep 20, 2026+671+462#9#4
Mon, Sep 21, 2026+389+240Not trending#14
Tue, Sep 22, 2026+148+131Not trendingNot trending
Wed, Sep 23, 2026+57+92Not trendingNot trending
Thu, Sep 24, 2026+49+61Not trendingNot trending
Fri, Sep 25, 2026+77+80Not trendingNot trending
Sat, Sep 26, 2026+37+80Not trendingNot trending
Sun, Sep 27, 2026+21+10Not trendingNot trending
Mon, Sep 28, 2026+27+40Not trendingNot trending
Tue, Sep 29, 2026+16+00Not trendingNot trending
Wed, Sep 30, 2026+77+30Not trendingNot trending
Thu, Oct 1, 2026+32+00Not trendingNot trending
Fri, Oct 2, 2026+13+30Not trendingNot trending
Sat, Oct 3, 2026+8+10Not trendingNot trending
Sun, Oct 4, 2026+11+10Not trendingNot trending
Mon, Oct 5, 2026+9+12Not trendingNot trending
Tue, Oct 6, 2026+32+40Not trendingNot trending
Wed, Oct 7, 2026+17+10Not trendingNot trending
Thu, Oct 8, 2026+24+10Not trendingNot trending
Fri, Oct 9, 2026+12+00Not trendingNot trending
Sat, Oct 10, 2026+8+00Not trendingNot trending
Sun, Oct 11, 2026+13+00Not trendingNot trending
Mon, Oct 12, 2026+13+10Not trendingNot trending
Tue, Oct 13, 2026+9+24Not trendingNot trending
Wed, Oct 14, 2026+12+03Not trendingNot trending
Thu, Oct 15, 2026+10+00Not trendingNot trending
Fri, Oct 16, 2026+11+20Not trendingNot trending
Sat, Oct 17, 2026+3+00Not trendingNot trending
Sun, Oct 18, 2026+5+00Not trendingNot trending
Mon, Oct 19, 2026+5+10Not trendingNot trending
Tue, Oct 20, 2026+3+10Not trendingNot trending
Wed, Oct 21, 2026+6+10Not trendingNot trending
Thu, Oct 22, 2026+2+00Not trendingNot trending
Fri, Oct 23, 2026+4+20Not trendingNot trending
Sat, Oct 24, 2026+1+00Not trendingNot trending
Sun, Oct 25, 2026+6+10Not trendingNot trending
Mon, Oct 26, 2026+3+00Not trendingNot trending
Tue, Oct 27, 2026+0+10Not trendingNot trending
Wed, Oct 28, 2026+3+00Not trendingNot trending
Thu, Oct 29, 2026+4+10Not trendingNot trending
Fri, Oct 30, 2026+6+00Not trendingNot trending
Sat, Oct 31, 2026+4+00Not trendingNot trending
Sun, Nov 1, 2026+1+00Not trendingNot trending
Mon, Nov 2, 2026+1+00Not trendingNot trending
Tue, Nov 3, 2026+3+00Not trendingNot trending
Wed, Nov 4, 2026+5+00Not trendingNot trending
Thu, Nov 5, 2026+1+00Not trendingNot trending
Total+2,062+18016
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Mentions and achievements

Where people are talking about bespokelabsai/nimble, and every badge it has earned
  1. Oct 41 post

    • Let Claude Code pick its own model/effort level (locally, no API key)

      Read full on Reddit

      r/ClaudeAI

  2. Oct 21 post

    • • Route requests to defined destinations • Check yes or no conditions with evidence • Rate outcomes on ordered levels

      Read full on X, posted by @the_osps

      @the_osps · x.com

  3. Sep 301 post

    • Nimble: Data, Model, Recipe for an Open Jev (From Bespoke Labs)

      Read full on Hacker News

      Hacker News

  4. 9 days earlier
  5. Sep 212 posts6 posts

    • who is kev? I need a link please.

      Read full on X, posted by @kweenbhacks

      @kweenbhacks · x.com

    • 用一个 9B 本地模型对文本做类型化判断，按你给的扁平 schema 直接返回选项和每个选项的概率，不写推理过程、不生成 JSON。

      Read full on X, posted by @QingQ77

      @QingQ77 · x.com

    • Nimble takes some text and a schema, and makes typed decisions about the text

      Read full on Hacker News

      Hacker News

    • 一个开放 Jev 的三件套，数据、模型、配方。 nimble 输入一段文本和一个 schema，输出带类型的判断。枚举字段支持 1 到 26 个选项，概率按你给的答案归一，模型是 9B。

      Read full on X, posted by @aigeeknews

      @aigeeknews · x.com

    • Wow open source devs exploded against jev, some calling it a joke given the amount of hype that was created there seems to be dozens of projects that achieve the same performance for free even…

      Read full on X, posted by @raythurnvoid

      @raythurnvoid · x.com

    • 把文本判断改成“只在候选答案里打分”，Nimble 这个思路很值得借鉴。 它用枚举或布尔 schema 固定输出空间，读取候选 token 的 logits 生成类型化结果和概率，不必生成再解析 JSON。更关键的是，对比式数据只改一个事实并翻转标签，训练模型识别真正影响决策的证据。适合路由、规则核验、分级；但不生成解释，也不适合嵌套决策。

      Read full on X, posted by @vintcessun

      @vintcessun · x.com

  6. Sep 201 post

    • 开源社区又从不同模式复刻了4个版本的jev。有用bert的编码模型的，也有修改llm，还有采用扩散模型的。 ❶ Laya — ModernBERT 系编码器 421M + PPO 训练 ❷ DiffusionGemmaJev — 用扩散模型再现。基准测试接近 ❸ Bespoke Nimble — Qwen3.5-9B 的 LoRA。自评 90%（原版 93%） ❹ Jevlike — 嵌入…

      Read full on X, posted by @alacheng

      @alacheng · x.com

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