Spaces:
Running
Running
| title: README | |
| emoji: 📊 | |
| colorFrom: red | |
| colorTo: yellow | |
| sdk: static | |
| pinned: false | |
| ## Hello, we're Minish! | |
| We're a two-person ([@pringled](https://github.com/Pringled) and [@stephantul](https://github.com/stephantul)) open-source lab, with a focus on Natural Language Processing. | |
| We believe that if you make models fast enough, you unlock new possibilities. | |
| Using our software, you can: | |
| * Embed the entire English Wikipedia in 5 minutes | |
| * Classify tens of thousands of documents per second on a CPU | |
| * Approximately deduplicate extremely large datasets in minutes | |
| * Build the fastest RAG application in the world | |
| * Easily evaluate which ANN algorithm works best for your data | |
| Our projects: | |
| * [model2vec](https://github.com/MinishLab/model2vec): tiny static embedding models with state-of-the-art performance. | |
| * [potion](https://huggingface.co/collections/minishlab/potion-6721e0abd4ea41881417f062): the best small models in the world. 100-500x faster than a sentence-transformer, and almost as good. | |
| * [vicinity](https://github.com/MinishLab/vicinity): consistent interfaces to many approximate nearest neighbor algorithms. | |
| * [semhash](https://github.com/MinishLab/semhash): lightning-fast, super accuracte, semantic deduplication and filtering for your text datasets. | |
| * [model2vec-rs](https://github.com/MinishLab/model2vec-rs): a Rust port of model2vec. | |
| You can also find us on: | |
| 🔬 [GitHub](https://github.com/MinishLab) | |
| 👽 [LinkedIn](https://www.linkedin.com/company/minish-lab/) | |
| 💬 [Discord](https://discord.gg/4BDPR5nmtK) | |