Who's Who of AI

Daniel van Strien

Machine Learning Librarian at Hugging Face

254 trust practitioner @danielvanstrien.bsky.social · 4,582 followers
AI research
Why they matter

Machine Learning Librarian at Hugging Face with public evidence across AI research.

AI signals
6
past 30d
Sources
1
distinct domains
Discusiones
2
past 30d
Latest signal
7d ago
View every signal from Daniel van Strien →
Machine Learning Librarian at @hf.co
What they're sharing

Articles & links

Got a digitised collection that needs OCR? uv-scripts is a set of single-file Python scripts that OCR a whole image dataset to markdown in one command — 20+ open VLMs to pick from, nothing to install but uv. github.com/davanstrien/...

GitHub - davanstrien/uv-scripts-for-ai: Self-contained UV scripts for data & ML tasks — OCR, vision, audio & more — run one in a command, locally or on Hugging Face Jobs. Built for humans and agents. github.com
AI Weekly's analysis →
  • Each script is a self-contained Python file using PEP 723 inline dependency declarations, runnable with a single `uv run` command.
  • Nine task categories are covered including OCR with 30+ models, audio transcription, vision detection, embeddings, and LLM inference.
  • Scripts use standardized argument patterns so both humans and AI agents can run them locally or on Hugging Face Jobs GPU infrastructure.
Read full analysis →
View on Bluesky · ♥ 38 ↻ 13 ↩ 1 · 2 from the directory shared this · 69d ago

A new @hf.co and @eleutherai.bsky.social project, with @storytracer.com! Blog post: huggingface.co/blog/fineboo...

FineBooks: are open OCR models good enough to unlock historical knowledge? huggingface.co
AI Weekly's analysis →
  • Hugging Face and EleutherAI's FineBooks leaderboard scores 14 open OCR models against 2,165 expert-transcribed pages from the Biodiversity Heritage Library.
  • dots.mocr (3B) tops the leaderboard at 97.6% reading accuracy, with sub-2B models OvisOCR2 and PaddleOCR-VL-1.6 close behind at under half a dollar per thousand pages.
  • Leading models are good enough for LLM training corpora but silently modernize archaic letterforms, ruling them out for faithful scholarly transcription.
Read full analysis →
View on Bluesky · ♥ 4 ↻ 2 ↩ 1 · 2 from the directory shared this · 7d ago

Public data on which coding agents actually use the Hugging Face Hub, refreshed monthly. Claude Code now sends a majority of everything the Hub can attribute to a named agent. In May, it led on 4 days out of 30. In July, all 30. huggingface.co/datasets/hug...

huggingface/agent-usage · Datasets at Hugging Face huggingface.co
AI Weekly's analysis →
  • Claude Code led July 2026 Hub agent traffic at 44.4% of requests and 39.5% of distinct users, with Codex second at 20.8% and 21.2%.
  • Hugging Face publishes only relative shares, not raw counts, so falling percentages do not indicate declining usage.
  • Attribution runs through the huggingface_hub Python library's User-Agent token, so direct HTTP calls and unregistered harnesses are excluded.
Read full analysis →
View on Bluesky · ♥ 13 ↻ 2 ↩ 4 · 2 from the directory shared this · 15d ago

Small open models are getting genuinely good at document parsing: OvisOCR2 (0.9B, Apache 2.0) is claiming SOTA on OmniDocBench v1.6. Day-1 recipe: OCR a whole HF image dataset — digitised newspapers, archives, zines — to markdown with one command. huggingface.co/datasets/uv-sc…

uv-scripts/ocr · Datasets at Hugging Face huggingface.co
View on Bluesky · ♥ 34 ↻ 2 ↩ 0 · 34d ago
Their own posts

Recent commentary

I think VLM-based OCR might finally be close to working on historic newspapers! Many models I've tried before failed i.e. hallucinations, repetition loops, context overflow. Surya OCR 2 (a 650M model!) does a very good job!

View on Bluesky · ♥ 87 ↻ 14 ↩ 1 · 56d ago

NuExtract3 (4B, Apache-2.0) does OCR *and* structured extraction. Point it at a dataset of scanned index cards + a JSON schema → clean catalog JSON One command on huggingface Jobs. (or skip the schema for plain Markdown OCR) Script + dataset 👇

View on Bluesky · ♥ 39 ↻ 13 ↩ 2 · 89d ago

If libraries, archives and museums pooled their (labelled) data, they could build state-of-the-art open models for the things they actually care about! I tried a small version: one open model (NuExtract-3, 4B) fine-tuned to read archival index cards across several collections.

View on Bluesky · ♥ 28 ↻ 5 ↩ 1 · 54d ago

FineBooks wants to help re-OCR the public domain to unlock a rich source of data for AI, for researchers, and for enjoyment. Step one: work out which modern OCR models are actually good enough.

View on Bluesky · ♥ 25 ↻ 5 ↩ 2 · 7d ago

What could a rich ecosystem of small GLAM AI models enable? IMO: cheaper, better-fitted, more robust models. Example: I extended an existing @natlibscot.bsky.social archival card detector to 4 collections to make a more generic index card detector. Took an hour or two and minimal $

View on Bluesky · ♥ 14 ↻ 1 ↩ 1 · 77d ago
Their network

In Daniel van Strien's orbit

Center = Daniel van Strien. Left = members they follow (green edges). Right = members who follow them (blue edges). Top = mutual follows (orange edges, slightly larger). Drag any node to reposition; click to open that profile.