{"id":15293020,"url":"https://github.com/argilla-io/biome-text","last_synced_at":"2025-10-07T06:30:31.716Z","repository":{"id":47210007,"uuid":"173919877","full_name":"argilla-io/biome-text","owner":"argilla-io","description":"Custom Natural Language Processing with big and small models 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align=\"center\"\u003e\n    \u003cbr\u003e\n    \u003cimg src=\"https://github.com/recognai/biome-text/raw/master/docs/biome_text_logo_for_readme.png\" width=\"600\"/\u003e\n    \u003cbr\u003e\n\u003cp\u003e\n\u003cp align=\"center\"\u003e\n    \u003ca href=\"https://github.com/recognai/biome-text/actions\"\u003e\n        \u003cimg alt=\"CI\" src=\"https://github.com/recognai/biome-text/workflows/CI/badge.svg?branch=master\u0026event=push\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://codecov.io/gh/recognai/biome-text\"\u003e\n        \u003cimg src=\"https://codecov.io/gh/recognai/biome-text/branch/master/graph/badge.svg?token=943463Z6F7\"/\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://github.com/recognai/biome-text/blob/master/LICENSE.txt\"\u003e\n        \u003cimg alt=\"GitHub\" src=\"https://img.shields.io/github/license/recognai/biome-text.svg?color=blue\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://www.recogn.ai/biome-text/\"\u003e\n        \u003cimg alt=\"Documentation\" src=\"https://img.shields.io/website/http/recognai.github.io/biome-text/index.html.svg?down_color=red\u0026down_message=offline\u0026up_message=online\"\u003e\n    \u003c/a\u003e\n    \u003ca href=\"https://github.com/recognai/biome-text/releases\"\u003e\n        \u003cimg alt=\"GitHub release\" src=\"https://img.shields.io/github/release/recognai/biome-text.svg\"\u003e\n    \u003c/a\u003e\n\u003c/p\u003e\n\n\u003ch3 align=\"center\"\u003e\n\u003cp\u003eNatural Language Processing library built with AllenNLP\n\u003c/h3\u003e\n\n## Quick Links\n- [Documentation](https://recognai.github.io/biome-text/)\n\n\n## Features\n* State-of-the-art and not so state-of-the-art models trained with **your own data** with simple workflows.\n\n* **Efficient data reading** for (large) datasets in multiple formats and sources (CSV, Parquet, JSON, etc.).\n\n* **Modular configuration and extensibility** of models, datasets and training runs programmatically or via config files.\n\n* Use via **`cli`** or as plain Python (e.g., inside a Jupyter Notebook)\n\n* **Compatible with AllenNLP**\n\n## Installation\n\nFor the installation we recommend setting up a fresh [conda](https://docs.conda.io/en/latest/miniconda.html) environment:\n\n```shell script\nconda create -n biome python~=3.7.0 pip\u003e=20.3.0\nconda activate biome\n```\n\nOnce the conda environment is activated, you can install the latest release via pip:\n\n````shell script\npip install -U biome-text\n````\n\nAfter installing *biome.text*, the best way to test your installation is by running the *biome.text* cli command:\n\n```shell script\nbiome --help\n```\n\n## Get started\n\nThe best way to see how *biome.text* works is to go through our [first tutorial](https://recognai.github.io/biome-text/master/documentation/tutorials/1-Training_a_text_classifier.html).\n\nPlease refer to our [documentation](https://recognai.github.io/biome-text) for more tutorials, detailed user guides and how you can [contribute](https://recognai.github.io/biome-text/master/documentation/community/1-contributing.html) to *biome.text*.\n\n## Licensing\n\nThe code in this project is licensed under Apache 2 license.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fargilla-io%2Fbiome-text","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fargilla-io%2Fbiome-text","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fargilla-io%2Fbiome-text/lists"}