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authorCoprDistGit <infra@openeuler.org>2023-05-10 06:04:44 +0000
committerCoprDistGit <infra@openeuler.org>2023-05-10 06:04:44 +0000
commit2eca3ca5ac537acd120e720e50ebaa3e8132f3f6 (patch)
tree3a1ff63fb08752d62b245e634c8dbedcd932f519
parentc6c914da610a49c0b0a62024d1b428e456df0d61 (diff)
automatic import of python-happytransformer
-rw-r--r--.gitignore1
-rw-r--r--python-happytransformer.spec286
-rw-r--r--sources1
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diff --git a/.gitignore b/.gitignore
index e69de29..f15ffaa 100644
--- a/.gitignore
+++ b/.gitignore
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+/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
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+%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 <Python_Bot@openeuler.org> - 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