[HN Gopher] Show HN: Create-LLM - Train your own LLM in 60 seconds
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       Show HN: Create-LLM - Train your own LLM in 60 seconds
        
       https://medium.com/@theaniketgiri/three-months-ago-i-wanted-...
        
       Author : theaniketgiri
       Score  : 36 points
       Date   : 2025-10-26 09:53 UTC (13 hours ago)
        
 (HTM) web link (github.com)
 (TXT) w3m dump (github.com)
        
       | kk58 wrote:
       | Does this work on mac
        
         | theaniketgiri wrote:
         | Yep, works fine on Mac. Try the nano or tiny templates if you
         | want quicker training runs
        
       | efilife wrote:
       | 2 questions: how much of this project is AI generated and how
       | much of only the readme is AI generated?
        
         | theaniketgiri wrote:
         | Mostly the repetitive stuff like README generation and pushing
         | code with meaningful commit messages was handled by AI. The
         | actual work and logic were done by me.
        
           | joshribakoff wrote:
           | What about the commit that added tens of thousands of lines
           | of markdown claiming to be an AI summary?
           | 
           | Or the meaningful commit message of "."
           | 
           | And the commit editing 1,000s of lines of python code
           | mislabeled as a docs change?
        
             | theaniketgiri wrote:
             | Totally fair question!
             | 
             | Docs / Markdown: AI handled repetitive stuff like READMEs
             | and summaries.
             | 
             | Core logic / Python: fully written by me.
             | 
             | Commit messages: some minimal ones just for quick
             | iterations -- the real work is in the code.
             | 
             | AI helped with boilerplate so I could ship faster; all
             | functionality is hand-crafted.
        
               | joshribakoff wrote:
               | If the AI did the boilerplate that implies it was not
               | fully written by you.
               | 
               | The "meaningful commit messages" -- again are a single
               | period as the message for a single commit for the entire
               | python portion of the codebase.
               | 
               | My question was rhetorical. Whether the AI did it or a
               | human did, it burns credibility to refer to things that
               | don't exist (like "meaningful commit messages")
        
               | teruakohatu wrote:
               | Hacker News is a better place when we don't attack people
               | sharing their work. Your point was made.
               | 
               | Well done to the author for shipping code. I look forward
               | to trying it out.
        
       | darepublic wrote:
       | I don't quite understand how you get from this:
       | 
       | > I wanted to understand how these things work by building one
       | myself.
       | 
       | Directly to this:
       | 
       | What if training an LLM was as easy as npx create-next-app?
       | 
       | I mean that the second thought seems to be the opposite of the
       | first (what if the entirety of training llm was abstracted behind
       | a simple command)
        
         | theaniketgiri wrote:
         | Great question - I should've been clearer.
         | 
         | When I started, I wanted to understand LLMs deeply. But I hit a
         | wall: tutorials were either "hello world" toys or "here's 500
         | lines of setup before you start."
         | 
         | What I needed was: "give me working code quickly, THEN let me
         | modify and learn."
         | 
         | That's what create-llm does. It scaffolds the boilerplate (like
         | create-next-app), so you can spend time learning the
         | interesting parts: - Why does vocab size matter? (adjust
         | config, see results) - What causes overfitting? (train on small
         | data, see it happen) - How do different architectures perform?
         | (swap templates, compare)
         | 
         | It's "easy to start, deep to master." The abstraction gets you
         | running in 60 seconds, then you dig into the code
        
       | seg_lol wrote:
       | The blogpost is some of the best LLM greentext I have seen for
       | targeting the hn hivemind. Everything about this is :chefs kiss:
        
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       (page generated 2025-10-26 23:01 UTC)