From 2eca3ca5ac537acd120e720e50ebaa3e8132f3f6 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Wed, 10 May 2023 06:04:44 +0000 Subject: automatic import of python-happytransformer --- .gitignore | 1 + python-happytransformer.spec | 286 +++++++++++++++++++++++++++++++++++++++++++ sources | 1 + 3 files changed, 288 insertions(+) create mode 100644 python-happytransformer.spec create mode 100644 sources diff --git a/.gitignore b/.gitignore index e69de29..f15ffaa 100644 --- a/.gitignore +++ b/.gitignore @@ -0,0 +1 @@ +/happytransformer-2.4.1.tar.gz diff --git a/python-happytransformer.spec b/python-happytransformer.spec new file mode 100644 index 0000000..104f81a --- /dev/null +++ b/python-happytransformer.spec @@ -0,0 +1,286 @@ +%global _empty_manifest_terminate_build 0 +Name: python-happytransformer +Version: 2.4.1 +Release: 1 +Summary: Happy Transformer is an API built on top of Hugging Face's Transformer library that makes it easy to utilize state-of-the-art NLP models. +License: Apache 2.0 +URL: https://github.com/EricFillion/happy-transformer +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/7a/1c/01318ece577d3a7fdd6d9103dc6dcc9eaf20312aef76a3158c399ec8a207/happytransformer-2.4.1.tar.gz +BuildArch: noarch + +Requires: python3-torch +Requires: python3-tqdm +Requires: python3-transformers +Requires: python3-datasets +Requires: python3-sentencepiece +Requires: python3-protobuf +Requires: python3-dataclasses + +%description +[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) +[![Downloads](https://pepy.tech/badge/happytransformer)](https://pepy.tech/project/happytransformer) +[![Website shields.io](https://img.shields.io/website-up-down-green-red/http/shields.io.svg)](http://happytransformer.com) +![PyPI](https://img.shields.io/pypi/v/happytransformer) +[![](https://github.com/EricFillion/happy-transformer/workflows/build/badge.svg)](https://github.com/EricFillion/happy-transformer/actions) + +# Happy Transformer +**Documentation and news: [happytransformer.com](http://happytransformer.com)** + +New Course: Create a text generation web app. Also learn how to fine-tune GPT-Neo [link](https://www.udemy.com/course/nlp-text-generation-python-web-app/?couponCode=LAUNCH) + + +Join our Discord server: [![Support Server](https://img.shields.io/discord/839263772312862740.svg?label=Discord&logo=Discord&colorB=7289da&style=?style=flat-square&logo=appveyor)](https://discord.gg/psVwe3wfTb) + + + +![HappyTransformer](logo.png) + +Happy Transformer is an package built on top of [Hugging Face's transformer library](https://huggingface.co/transformers/) that makes it easy to utilize state-of-the-art NLP models. + +## Features + +| Public Methods | Basic Usage | Training | +|------------------------------------|--------------|------------| +| Text Generation | ✔ | ✔ | +| Text Classification | ✔ | ✔ | +| Word Prediction | ✔ | ✔ | +| Question Answering | ✔ | ✔ | +| Text-to-Text | ✔ | ✔ | +| Next Sentence Prediction | ✔ | | +| Token Classification | ✔ | | + +## Quick Start +```sh +pip install happytransformer +``` + +```python + +from happytransformer import HappyWordPrediction +#--------------------------------------# +happy_wp = HappyWordPrediction() # default uses distilbert-base-uncased +result = happy_wp.predict_mask("I think therefore I [MASK]") +print(result) # [WordPredictionResult(token='am', score=0.10172799974679947)] +print(result[0].token) # am +``` + +## Maintainers +- [Eric Fillion](https://github.com/ericfillion) Lead Maintainer +- [Ted Brownlow](https://github.com/ted537) Maintainer + +## Tutorials +[Text generation with training (GPT-Neo)](https://youtu.be/GzHJ3NUVtV4) + +[Text classification (training)](https://www.vennify.ai/train-text-classification-transformers/) + +[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) + +[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/) + + + + +%package -n python3-happytransformer +Summary: Happy Transformer is an API built on top of Hugging Face's Transformer library that makes it easy to utilize state-of-the-art NLP models. +Provides: python-happytransformer +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-happytransformer +[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) +[![Downloads](https://pepy.tech/badge/happytransformer)](https://pepy.tech/project/happytransformer) +[![Website shields.io](https://img.shields.io/website-up-down-green-red/http/shields.io.svg)](http://happytransformer.com) +![PyPI](https://img.shields.io/pypi/v/happytransformer) +[![](https://github.com/EricFillion/happy-transformer/workflows/build/badge.svg)](https://github.com/EricFillion/happy-transformer/actions) + +# Happy Transformer +**Documentation and news: [happytransformer.com](http://happytransformer.com)** + +New Course: Create a text generation web app. Also learn how to fine-tune GPT-Neo [link](https://www.udemy.com/course/nlp-text-generation-python-web-app/?couponCode=LAUNCH) + + +Join our Discord server: [![Support Server](https://img.shields.io/discord/839263772312862740.svg?label=Discord&logo=Discord&colorB=7289da&style=?style=flat-square&logo=appveyor)](https://discord.gg/psVwe3wfTb) + + + +![HappyTransformer](logo.png) + +Happy Transformer is an package built on top of [Hugging Face's transformer library](https://huggingface.co/transformers/) that makes it easy to utilize state-of-the-art NLP models. + +## Features + +| Public Methods | Basic Usage | Training | +|------------------------------------|--------------|------------| +| Text Generation | ✔ | ✔ | +| Text Classification | ✔ | ✔ | +| Word Prediction | ✔ | ✔ | +| Question Answering | ✔ | ✔ | +| Text-to-Text | ✔ | ✔ | +| Next Sentence Prediction | ✔ | | +| Token Classification | ✔ | | + +## Quick Start +```sh +pip install happytransformer +``` + +```python + +from happytransformer import HappyWordPrediction +#--------------------------------------# +happy_wp = HappyWordPrediction() # default uses distilbert-base-uncased +result = happy_wp.predict_mask("I think therefore I [MASK]") +print(result) # [WordPredictionResult(token='am', score=0.10172799974679947)] +print(result[0].token) # am +``` + +## Maintainers +- [Eric Fillion](https://github.com/ericfillion) Lead Maintainer +- [Ted Brownlow](https://github.com/ted537) Maintainer + +## Tutorials +[Text generation with training (GPT-Neo)](https://youtu.be/GzHJ3NUVtV4) + +[Text classification (training)](https://www.vennify.ai/train-text-classification-transformers/) + +[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) + +[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/) + + + + +%package help +Summary: Development documents and examples for happytransformer +Provides: python3-happytransformer-doc +%description help +[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) +[![Downloads](https://pepy.tech/badge/happytransformer)](https://pepy.tech/project/happytransformer) +[![Website shields.io](https://img.shields.io/website-up-down-green-red/http/shields.io.svg)](http://happytransformer.com) +![PyPI](https://img.shields.io/pypi/v/happytransformer) +[![](https://github.com/EricFillion/happy-transformer/workflows/build/badge.svg)](https://github.com/EricFillion/happy-transformer/actions) + +# Happy Transformer +**Documentation and news: [happytransformer.com](http://happytransformer.com)** + +New Course: Create a text generation web app. Also learn how to fine-tune GPT-Neo [link](https://www.udemy.com/course/nlp-text-generation-python-web-app/?couponCode=LAUNCH) + + +Join our Discord server: [![Support Server](https://img.shields.io/discord/839263772312862740.svg?label=Discord&logo=Discord&colorB=7289da&style=?style=flat-square&logo=appveyor)](https://discord.gg/psVwe3wfTb) + + + +![HappyTransformer](logo.png) + +Happy Transformer is an package built on top of [Hugging Face's transformer library](https://huggingface.co/transformers/) that makes it easy to utilize state-of-the-art NLP models. + +## Features + +| Public Methods | Basic Usage | Training | +|------------------------------------|--------------|------------| +| Text Generation | ✔ | ✔ | +| Text Classification | ✔ | ✔ | +| Word Prediction | ✔ | ✔ | +| Question Answering | ✔ | ✔ | +| Text-to-Text | ✔ | ✔ | +| Next Sentence Prediction | ✔ | | +| Token Classification | ✔ | | + +## Quick Start +```sh +pip install happytransformer +``` + +```python + +from happytransformer import HappyWordPrediction +#--------------------------------------# +happy_wp = HappyWordPrediction() # default uses distilbert-base-uncased +result = happy_wp.predict_mask("I think therefore I [MASK]") +print(result) # [WordPredictionResult(token='am', score=0.10172799974679947)] +print(result[0].token) # am +``` + +## Maintainers +- [Eric Fillion](https://github.com/ericfillion) Lead Maintainer +- [Ted Brownlow](https://github.com/ted537) Maintainer + +## Tutorials +[Text generation with training (GPT-Neo)](https://youtu.be/GzHJ3NUVtV4) + +[Text classification (training)](https://www.vennify.ai/train-text-classification-transformers/) + +[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) + +[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/) + + + + +%prep +%autosetup -n happytransformer-2.4.1 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-happytransformer -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed May 10 2023 Python_Bot - 2.4.1-1 +- Package Spec generated diff --git a/sources b/sources new file mode 100644 index 0000000..cda86df --- /dev/null +++ b/sources @@ -0,0 +1 @@ +f5fd9d928c226978b1a7542725edf827 happytransformer-2.4.1.tar.gz -- cgit v1.2.3