Making a vintage LLM from scratch; Take #2
Since then, I kept stubbornly working on this project EVERY.SINGLE.DAY, like an absolute maniac: finding new datasets, improving old datasets, reading papers, training models & tokenizers, and running an unreasonable number of experiments.This post is the report of what happened in the meantime. It's long, because a lot happened. tl;dr; {If you're in your lunch break and you don't have time to read this, or you want to know if this article is worth your time, this is the summary:I built a pile of new datasets, 3 new vintage models, a benchmark, an evaluation pipeline, and I'm starting fine-tuning for real. This is humbling and motivating!I don't have any ads and I'm getting exactly $0 from traffic, but your comments and ideas mean a lot to me, and I want to thank you.I sincerely hope you'll get lots of value from this article, at least as much as you got from the previous one.
- ▪Since then, I kept stubbornly working on this project EVERY.SINGLE.DAY, like an absolute maniac: finding new datasets, improving old datasets, reading papers, training models & tokenizers, and running an unreasonable number of experiments.T
- ▪It's long, because a lot happened. tl;dr; {If you're in your lunch break and you don't have time to read this, or you want to know if this article is worth your time, this is the summary:I built a pile of new datasets, 3 new vintage models,
- ▪This is humbling and motivating!I don't have any ads and I'm getting exactly $0 from traffic, but your comments and ideas mean a lot to me, and I want to thank you.I sincerely hope you'll get lots of value from this article, at least as muc
2 outlets in our directory ran this story, first to last over 8 hours. All of the coverage we found sits in one bucket: centre. That one-sidedness is itself worth noticing.
- ▪ NanoGPT-inference LLM inference from scratch — Research blog of Pieter Delobelle
Hacker News (AI / LLM) files mainly under ai. We currently carry 4,881 of its stories.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Cr;Lf; |
| Canonical URL | https://crlf.link/log/entries/260911-1/ |
| Publication time | Mon, 14 Sep 2026 19:52:34 +0000 |
| Retrieval time | 2026-09-14T20:06:51.582Z |
| Last seen | 2026-09-14T20:06:51.582Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | -AN_hknyK8DK · 2 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Making a vintage LLM from scratch; Take #2 2026 Sep 11, Fri 55 min Three and a half months ago I wrote about making my own vintage LLM from scratch, trained only on texts written before the year 1900.That project ended with a Llama-340M params base model that could write nice Victorian paragraphs, but couldn't hold a conversation in any way, shape, or form. Since then, I kept stubbornly working on this project EVERY.SINGLE.DAY, like an absolute maniac: finding new datasets, improving old datasets, reading papers, training models & tokenizers, and running an unreasonable number of experiments.This post is the report of what happened in the meantime. It's long, because a lot happened.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Cr;Lf;.
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