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analyticalrohit/llms-from-scratch

Build a ChatGPT like LLM from scratch in PyTorch, explained step by step.

#Learning resources#LLM training
Visit GitHub
Jupyter Notebook
384
92
1 contributors
MIT License
website
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How fast analyticalrohit/llms-from-scratch 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

Aug 20 – Oct 19, 2026

Stars +3 in 61 days

01
1

Forks +5 in 61 days

01
1

Merged PRs 0 in 61 days

01

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

Not in the Trendshift top 25 in this period

Aug 20Aug 28Sep 5Sep 13Sep 21Sep 29Oct 7Oct 15
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
Thu, Aug 20, 2026+0+00
Fri, Aug 21, 2026+0+00
Sat, Aug 22, 2026+0+00
Sun, Aug 23, 2026+0+00
Mon, Aug 24, 2026+0+00
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Thu, Aug 27, 2026+0+10
Fri, Aug 28, 2026+0+00
Sat, Aug 29, 2026+1+10
Sun, Aug 30, 2026+0+00
Mon, Aug 31, 2026+0+00
Tue, Sep 1, 2026+0+00
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Thu, Sep 3, 2026+0+00
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Fri, Sep 11, 2026+0+00
Sat, Sep 12, 2026+0+00
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Mon, Sep 14, 2026+0+00
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Fri, Sep 18, 2026+0+00
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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+1+00
Sun, Sep 27, 2026+0+10
Mon, Sep 28, 2026+0+00
Tue, Sep 29, 2026+0+10
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+0+00
Thu, Oct 8, 2026+0+10
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+0+00
Sun, Oct 18, 2026+0+00
Mon, Oct 19, 2026+0+00
Total+3+50
  • 1#1 on the list
  • 7Rank that day
  • Not trending
  • Mentions and achievements

    Where people are talking about analyticalrohit/llms-from-scratch, and every badge it has earned
    1. Jun 281 post
      • https://t.co/mfgVrdcR3L

        Read full on X, posted by @_rohit_tiwari_

        @_rohit_tiwari_ · x.com

    2. Jun 271 post
      • https://t.co/mfgVrdcR3L

        Read full on X, posted by @_rohit_tiwari_

        @_rohit_tiwari_ · x.com

    3. Jun 251 post
      • https://t.co/mfgVrdcR3L

        Read full on X, posted by @_rohit_tiwari_

        @_rohit_tiwari_ · x.com

    4. Jun 231 post
      • If you want to learn AI the right way, start here. No shortcuts. No hype. No fluff. Top 10 Stanford's Courses on AI & ML. CS221: Artificial Intelligence CS229: Machine Learning CS229M: Machine…

        Read full on X, posted by @_rohit_tiwari_

        @_rohit_tiwari_ · x.com

    5. Jun 221 post
      • This 115-page book unlocks the secrets of LLM fine tuning. A comprehensive guide which covers: > the fine-tuning process for LLMs > combining both theory and practice.

        Read full on X, posted by @_rohit_tiwari_

        @_rohit_tiwari_ · x.com

    6. Jun 202 posts
      • Can you really run GLM 5.2 locally? Technically, yes. GLM 5.2 has 744B params (40B active) and a 1M context window. The full model is ~1.5TB. Minimum memory requirements: > 1 bit: 223 GB > 2 bit: 245…

        Read full on X, posted by @_rohit_tiwari_

        @_rohit_tiwari_ · x.com

      • The best site on the internet for Harness Engineering, completely free. "The better the harness, the better the agent." AI coding agents are powerful but without the right controls. > they can be…

        Read full on X, posted by @_rohit_tiwari_

        @_rohit_tiwari_ · x.com

    7. Jun 191 post
      • Stanford AI, ML, and Math cheatsheets. Github (900+ stars): ➟ Artificial Intelligence ➟ Transformers and LLMs ➟ Machine Learning ➟ Deep Learning ➟ Probabilities & Statistics ➟ Algebra & Calculus

        Read full on X, posted by @_rohit_tiwari_

        @_rohit_tiwari_ · x.com

    8. Jun 181 post
      • AI Engineering from Scratch. 503 lessons. 20 phases. 320 hours. Phase 00: Setup & Tooling (12 lessons) Phase 01: Math Foundations (22 lessons) Phase 02: ML Fundamentals (18 lessons) Phase 03: Deep…

        Read full on X, posted by @_rohit_tiwari_

        @_rohit_tiwari_ · x.com

    9. Jun 151 post
      • Attention powers transformers and modern LLMs. Let’s build it from scratch: Step by step Self-Attention Self attention helps a model understand how words relate to each other in a sentence. Instead…

        Read full on X, posted by @_rohit_tiwari_

        @_rohit_tiwari_ · x.com

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