We’ve just released Semble v0.3.0!

Biggest changes:

- Automatic disk caching: First search builds the index; later searches are (much) faster.
- Search more than code: new `--content` flag for searching docs, config, code, or all of them together.

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- JSON output: CLI and MCP results are now structured JSON, making Semble easier to use from agents and scripts.
- Better file control: use `.sembleignore` to exclude files or force-include custom extensions.

Release notes: github.com/MinishLab/semb…

Today we're releasing Semble, a fast and accurate code search library built for agents 🤖!

We're also releasing potion-code-16M, a small code-specialized static embedding model that powers Semble.

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Main features:
- Fast: indexes a full codebase in ~250 ms and answers queries in ~1.5 ms, all on CPU
- Accurate: on par with transformers
- MCP server: drop-in tool for Claude Code, Cursor, Codex, OpenCode, and any other MCP-compatible agent
- Zero setup: no API keys, no GPU

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Semble: github.com/MinishLab/semb…

Benchmarks: github.com/MinishLab/semb…

How it works: github.com/MinishLab/semb…

Model: huggingface.co/minishlab/poti…

Model2Vec 0.7.0 is out now, as well as a blogpost on model size reduction techniques!

This release features a large number of ways to improve the distillation process.
- Vocabulary quantization
- Configurable pooling
- A number of small improvements and bugfixes

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We also have a new blogpost on model size reduction where we showcase how to reduce model size by a factor of 15, creating a 6MB model (!) without impacting performance.

Links:
Release notes: github.com/MinishLab/mode…

Blogpost: minish.ai/blog/2025-10-0…

semhash is so so so convenient and fast

We have a new website (and name): minish.ai

We’ve been working on an improved website for a while, and it’s finally here. It has documentation for all our packages as well as our blog. More things coming soon! 🚀

Some guy forked our "model2vec-rs" crate, and put it under the "model2vec" name on crates io and then didn't tell us about it. See here: crates.io/crates/model2v…

Like what's the goal here except name squatting.

We just released model2vec 0.6.0!

This is a big release, containing many big improvements 🔥

GitHub release: github.com/MinishLab/mode…

PyPi release: pypi.org/project/model2…

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- Model improvements: nearly all distilled models will perform better, especially in STS and clustering tasks. A while ago we published a blog post on modernbert not working, but we now found out why, and fixed it!

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- Smaller tokenizers: all tokenizers are now 40% smaller, at no cost to anyone.

A blog post with experimental results is coming in the next couple of days.

The deduplication Space by @minishlab just got a fresh update, allowing you to remove near duplicates in (training) datasets.

Details in 🧵

Do not sleep on deduplication! Use this FREE app for semantic deduplication of multiple massive datasets.

This is how it works:

- You pick one all more datasets from the Hub
- It make a semantic embedding of each row
- It remove removes near duplicates based on a threshold like deduplicated dataset back to a new repo, and get to work.

We just released tokenlearn 0.2.0! Tokenlearn is our post-distill distillation framework, and is what we use to train our potion models.

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All you need is ~100k-1M documents, a sentence transformer, and some time, and your static model will be a lot better than before. See the snippet below for the recipe that will reproduce potion-base-8m (you should use more than 500 docs though).

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Release notes: github.com/MinishLab/toke…