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README.md
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##
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We
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Our goal is to provide with usable and fun tools to make working with language data easy and fun.
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* We like "classical" nlp and machine learning, so no LLM interfaces here.
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* We like cpu-bound work, not everyone has access to GPUs or wants to pay big tech companies for using GPUs.
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* We try to be as multi-lingual as possible: NLP work tends to focus purely on English, to the detriment of other languages.
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* We write in Python, and use a pretty opinionated stack (uv, everything fully typed, everything fully documented, no exceptions).
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* We try to be inclusive: if you'd like to help out, please let us know π€.
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* Easy to use βοΈ
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* Fun to use π₯³
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* Opinionated π€
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* Open for integration π§²
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* Original (does not re-invent the wheel) π€Έ
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* Fast π΄
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You can also find us on:
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π¬ [GitHub](https://github.com/MinishLab)
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## Hello, we're minish!
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We're a two-person ([@pringled](https://github.com/Pringled) and [@stephantul](https://github.com/stephantul)) open-source company, with a focus on Natural Language Processing.
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We believe that if you make models fast enough, you unlock new possibilities.
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Using our software, you can:
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* Ingest the entire English Wikipedia in 5 minutes
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* Classify tens of thousands of documents per second on CPU
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* Approximately deduplicate extremely large datasets in minutes
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* Build the fastest RAG application in the world
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* Easily evaluate which ANN algorithm works best for your data
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Our projects:
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* [model2vec](https://github.com/MinishLab/model2vec): make tiny models that are still really really good.
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* [potion](https://huggingface.co/minishlab/potion-base-8M): the best small model in the world. 100-500x faster than a sentence-transformer, and almost as good.
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* [vicinity](https://github.com/MinishLab/vicinity): consistent interfaces to many approximate nearest neighbor algorithms.
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* [semhash](https://github.com/MinishLab/semhash): lightning-fast, super accuracte, approximate deduplication for your text datasets.
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You can also find us on:
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π¬ [GitHub](https://github.com/MinishLab)
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