Metadata-Version: 2.4
Name: happytransformer
Version: 3.0.1
Summary: Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.
Author-email: The Happy Transformer Development Team <happytransformer@gmail.com>
License: Apache 2.0
Project-URL: Homepage, https://happytransformer.com
Project-URL: Repository, https://github.com/EricFillion/happy-transformer
Keywords: ai,transformer,happy,HappyTransformer,classification,nlp,nlu,training,fine-tuning
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch>=2.2
Requires-Dist: tqdm>=4.43
Requires-Dist: transformers<5.0.0,>=4.46.0
Requires-Dist: datasets<3.0.0,>=2.15.0
Requires-Dist: dataclasses; python_version < "3.7"
Requires-Dist: sentencepiece
Requires-Dist: protobuf
Requires-Dist: accelerate<2.0.0,>=1.3.0
Requires-Dist: tokenizers<1.0.0,>=0.20.0
Requires-Dist: wandb
Dynamic: license-file

<!-- HEADER -->
<h1 align="center">
  HAPPY TRANSFORMER
</h1>

<p align="center">
  <img src="https://raw.githubusercontent.com/EricFillion/happy-transformer/master/logo.png" alt="Happy Transformer logo" width="200">
</p>

<!-- BADGES -->
<p align="center">
  <a href="https://opensource.org/licenses/Apache-2.0">
    <img src="https://img.shields.io/badge/License-Apache%202.0-blue.svg" alt="License: Apache-2.0" height="20">
  </a>
  <a href="https://pepy.tech/project/happytransformer">
    <img src="https://pepy.tech/badge/happytransformer" alt="Downloads" height="20">
  </a>
  <img src="https://img.shields.io/pypi/v/happytransformer" alt="PyPI" height="20">
  <a href="https://discord.gg/psVwe3wfTb">
    <img src="https://img.shields.io/discord/839263772312862740.svg?label=Discord&logo=Discord&colorB=7289da" alt="Discord" height="20">
  </a>
</p>

<!-- SITE LINK -->
<p align="center">
  <strong><a href="https://happytransformer.com">happytransformer.com</a></strong>
</p>

<!-- DIVIDER -->
<hr>


Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.


## Upcoming Version 4.0.0 

Version 4.0.0 is in the final stages of development. 
It's a complete rewrite of the library with many new features.
It includes breaking changes, and so we recommend you set the version to <4.0.0 in your requirements.   


## Tasks 

| Tasks                    | Inference | Training   |
|--------------------------|-----------|------------|
| Text Generation          | ✔         | ✔          |
| Text Classification      | ✔         | ✔          | 
| Word Prediction          | ✔         | ✔          |
| Question Answering       | ✔         | ✔          | 
| Text-to-Text             | ✔         | ✔          | 
| Next Sentence Prediction | ✔         |            | 
| Token Classification     | ✔         |            | 

Note: word prediction, question answering, next sentence prediction and token classification have been deprecated. 

## Install
```sh
pip install "happytransformer<4.0.0"
```


## Maintainers
- [Eric Fillion](https://github.com/ericfillion)  Lead Maintainer
- [Ted Brownlow](https://github.com/ted537) Maintainer


## Tutorial Articles

[Text classification (training)](https://www.vennify.ai/train-text-classification-transformers/) 

[Top T5 Models ](https://www.vennify.ai/top-t5-transformer-models/)

[Grammar Correction](https://www.vennify.ai/grammar-correction-python/)

[Fine-tune a Grammar Correction Model](https://www.vennify.ai/fine-tune-grammar-correction/)

## Tutorial Videos

[Text generation with training (GPT-Neo)](https://youtu.be/GzHJ3NUVtV4)

[Text classification (hate speech detection)](https://youtu.be/jti2sPQYzeQ) 

[Text classification (sentiment analysis)](https://youtu.be/Ew72EAgM7FM)

[Word prediction with training (DistilBERT, RoBERTa)](https://youtu.be/AWe0PHsPc_M)
