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simpleT5

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simpleT5 is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.

파일 탐색기

최종 버전 다운로드 (.zip)

- - python-package.yml
- simplet5.png
- st5.png
- simpleT5-summarization.ipynb
- __init__.py
- simplet5.py
.gitignore
LICENSE
README.md
requirements.txt
setup.py

# 설치 가이드

1. 코드 내려받기

git clone https://github.com/Shivanandroy/simpleT5

깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.

cd simpleT5

방금 내려받은 프로젝트 폴더 안으로 이동합니다.

2. 공식 설치 스크립트

쉬움 추천

사전 준비물

Python 3 pip 명령어를 쓰려면 Python이 필요합니다.

pip install --upgrade simplet5

PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.

✅ 설치 후 새 터미널을 열고, 프로그램의 버전 확인 명령(예: --version)으로 정상 설치됐는지 확인하세요.

이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.

3. Python

쉬움

사전 준비물

Git GitHub에서 프로젝트 코드를 내려받으려면 필요합니다.
Python 3 설치 시 'Add Python to PATH' 옵션을 꼭 체크하세요 (Windows).

pip install --upgrade simplet5

PyPI에 배포된 패키지를 바로 설치합니다. 소스 클론이 필요 없습니다.

✅ 에러 메시지 없이 실행되고 터미널에 안내 문구가 출력되면 정상입니다.

이 레포의 README에 적힌 실제 명령어를 그대로 가져왔습니다.

// repository documentation

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<img align="center" src="data/st5.png" alt="simpleT5">

<p align="center">
<b>Quickly train T5/mT5/byT5/CodeT5 models in just 3 lines of code
</b>
</p>
<p align="center">
<a href="https://badge.fury.io/py/simplet5"><img src="https://badge.fury.io/py/simplet5.svg" alt="PyPI version" height="18"></a>

<a href="https://badge.fury.io/py/simplet5">
        <img alt="Stars" src="https://img.shields.io/github/stars/Shivanandroy/simpleT5?color=blue">
    </a>
<a href="https://pepy.tech/project/simplet5">
        <img alt="Stats" src="https://static.pepy.tech/personalized-badge/simplet5?period=total&units=international_system&left_color=black&right_color=brightgreen&left_text=Downloads">
    </a>
<a href="https://opensource.org/licenses/MIT">
        <img alt="License" src="https://img.shields.io/badge/License-MIT-yellow.svg">
    </a>
</p>

**simpleT5** is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.
> T5 models can be used for several NLP tasks such as summarization, QA , QG , translation , text generation, and more.

Here's a link to [Medium article](https://snrspeaks.medium.com/simplet5-train-t5-models-in-just-3-lines-of-code-by-shivanand-roy-2021-354df5ae46ba) along with an [example colab notebook](https://colab.research.google.com/drive/1JZ8v9L0w0Ai3WbibTeuvYlytn0uHMP6O?usp=sharing)

## Install
```python
# It's advisable to create a new python environment and install simplet5
pip install --upgrade simplet5
```

## Usage 
**simpleT5** for summarization task [![Open In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1JZ8v9L0w0Ai3WbibTeuvYlytn0uHMP6O?usp=sharing)
```python
# import
from simplet5 import SimpleT5

# instantiate
model = SimpleT5()

# load (supports t5, mt5, byT5 and CodeT5 models)
model.from_pretrained("t5","t5-base")

# train
model.train(train_df=train_df, # pandas dataframe with 2 columns: source_text & target_text
            eval_df=eval_df, # pandas dataframe with 2 columns: source_text & target_text
            source_max_token_len = 512, 
            target_max_token_len = 128,
            batch_size = 8,
            max_epochs = 5,
            use_gpu = True,
            outputdir = "outputs",
            early_stopping_patience_epochs = 0,
            precision = 32
            )

# load trained T5 model
model.load_model("t5","path/to/trained/model/directory", use_gpu=False)

# predict
model.predict("input text for prediction")

```
## Articles
- [Geek Culture: simpleT5 — Train T5 Models in Just 3 Lines of Code](https://medium.com/geekculture/simplet5-train-t5-models-in-just-3-lines-of-code-by-shivanand-roy-2021-354df5ae46ba)
- [Abstractive Summarization with SimpleT5⚡️](https://snrspeaks.medium.com/abstractive-summarization-with-simplet5-%EF%B8%8F-344a78f73265)
- [Training T5 model in just 3 lines of Code with ONNX Inference](https://medium.com/mlearning-ai/training-t5-model-in-just-3-lines-of-code-with-onnx-inference-ff5b6678c757)
- [Kaggle: simpleT5⚡️ -  Generating one line summary of papers](https://www.kaggle.com/mathurinache/simplet5-generating-one-line-summary-of-papers)
- [Youtube: Abstractive Summarization Demo with SimpleT5](https://www.youtube.com/watch?v=jgKj-7v2UYU)

## Acknowledgements
- [Transformers by HuggingFace 🤗](https://huggingface.co/transformers/)
- [Pytorch Lightning ⚡️](https://www.pytorchlightning.ai/)
- [Fastt5](https://github.com/Ki6an/fastT5)