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Text2Text Language Modeling Toolkit
| Date | Stars |
|---|---|
| 2026-07-24 | 304 |
| 2026-07-25 | 304 |
| 2026-07-28 | 304 |
| 2026-07-30 | 304 |
| 2026-07-31 | 304 |
| 2026-08-06 | 304 |
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# Text2Text Language Modeling Toolkit
<details>
<summary>Overview</summary>
* [Colab Notebooks](https://github.com/artitw/text2text#colab-notebooks)
* [Installation Requirements](https://github.com/artitw/text2text#installation-requirements)
* [Quick Start Guide](https://github.com/artitw/text2text#api-quick-start-guide)
* [Languages Available](https://github.com/artitw/text2text#languages-available)
* [Requirements & Installation](https://github.com/artitw/text2text#requirements-and-installation)
* [Examples](https://github.com/artitw/text2text#examples)
* [Assistant](https://github.com/artitw/text2text#assistant)
* [Tokenization](https://github.com/artitw/text2text#tokenization)
* [Embedding](https://github.com/artitw/text2text#embedding--vectorization)
* [TF-IDF](https://github.com/artitw/text2text#tf-idf)
* [BM25](https://github.com/artitw/text2text#bm25)
* [Index](https://github.com/artitw/text2text#index)
* [Distance](https://github.com/artitw/text2text#levenshtein-sub-word-edit-distance)
* [Translation](https://github.com/artitw/text2text#translation)
* [Data Augmentation](https://github.com/artitw/text2text#data-augmentation--back-translation)
* [Identification](https://github.com/artitw/text2text#identification)
* [Questions?](https://github.com/artitw/text2text#questions)
* [Citation](https://github.com/artitw/text2text#citation)
* [Contributing](https://github.com/artitw/text2text#contributing)
* [Code of Conduct](https://github.com/artitw/text2text#code-of-conduct)
</details>
## Colab Notebooks
* Assistant (free private ChatGPT LLM alternative) [](https://colab.research.google.com/drive/1K6Kk80w9vjFZ7PL9dPRgVuOPuaWcY4ae?usp=sharing)
* STF-IDF multilingual search [](https://colab.research.google.com/drive/1RaWj5SqWvyC2SsCTGg8IAVcl9G5hOB50?usp=sharing)
* All examples [](https://colab.research.google.com/drive/1LE_ifTpOGO5QJCKNQYtZe6c_tjbwnulR)
## Installation Requirements
```
pip install -qq -U text2text
```
* [Examples](#examples) run with <16 GB RAM on free [Colab GPUs](https://colab.research.google.com/drive/1LE_ifTpOGO5QJCKNQYtZe6c_tjbwnulR).
## Quick Start Guide
Functionality | Invocation | Result
:------------: | :-------------: | :-------------:
Module Importing | `import text2text as t2t` | Libraries imported
[Assistant](https://github.com/artitw/text2text#assistant) | `t2t.Assistant().transform("Describe Text2Text in a few words: ")` | `['Text2Text is an AI-powered text generation tool that creates coherent and continuous text based on prompts.']`
[Language Model Setting](https://github.com/artitw/text2text#byot-bring-your-own-translator) | `t2t.Transformer.PRETRAINED_TRANSLATOR = "facebook/m2m100_418M"` | Change from default
[Tokenization](https://github.com/artitw/text2text#tokenization) | `t2t.Tokenizer().transform(["Hello, World!"])` | `[['▁Hello', ',', '▁World', '!']]`
[Embedding](https://github.com/artitw/text2text#embedding--vectorization) | `t2t.Vectorizer().transform(["Hello, World!"])` | `[[0.18745188, 0.05658336, ..., 0.6332584 , 0.43805206]]`
[TF-IDF](https://github.com/artitw/text2text#tf-idf) | `t2t.Tfidfer().transform(["Hello, World!"])` | `[{'!': 0.5, ',': 0.5, '▁Hello': 0.5, '▁World': 0.5}]`
[BM25](https://github.com/artitw/text2text#bm25) | `t2t.Bm25er().transform(["Hello, World!"])` | `[{'!': 0.3068528194400547, ',': 0.3068528194400547, '▁Hello': 0.3068528194400547, '▁World': 0.3068528194400547}]`
[Indexer](https://github.com/artitw/text2text#index) | `index = t2t.Indexer().transform(["Hello, World!"])` | Index object for information retrieval
[Translation](https://github.com/artitw/text2text#translation) | `t2t.Translater().transform(["Hello, World!"], src_lang="en, tgt_lang="zh")` | `['你好,世界!']`
[Data Augmentation](https://github.com/artitw/tExcerpt of 47,640 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e18000e575fc5e57, topic:nlp, topic:tokenizer, readme:tokenizer
matched fp:e18000e575fc5e57, topic:llm, topic:llama
matched fp:e18000e575fc5e57, topic:embeddings
matched fp:e18000e575fc5e57, topic:chatbot, topic:chatgpt