blob: c35a9241e062b5249aa46a1ed224cdf4487ef47e (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
|
%global _empty_manifest_terminate_build 0
Name: python-simpletransformers
Version: 0.63.9
Release: 1
Summary: An easy-to-use wrapper library for the Transformers library.
License: Apache Software License
URL: https://github.com/ThilinaRajapakse/simpletransformers/
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a2/a8/229be18dae36693e2e8f6f1fe4ecfed0b4c8ed6e79a3a493cb6868167815/simpletransformers-0.63.9.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-requests
Requires: python3-tqdm
Requires: python3-regex
Requires: python3-transformers
Requires: python3-datasets
Requires: python3-scipy
Requires: python3-scikit-learn
Requires: python3-seqeval
Requires: python3-tensorboard
Requires: python3-pandas
Requires: python3-tokenizers
Requires: python3-wandb
Requires: python3-streamlit
Requires: python3-sentencepiece
%description
## Current Pretrained Models
For a list of pretrained models, see [Hugging Face docs](https://huggingface.co/pytorch-transformers/pretrained_models.html).
The `model_types` available for each task can be found under their respective section. Any pretrained model of that type
found in the Hugging Face docs should work. To use any of them set the correct `model_type` and `model_name` in the `args`
%package -n python3-simpletransformers
Summary: An easy-to-use wrapper library for the Transformers library.
Provides: python-simpletransformers
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-simpletransformers
## Current Pretrained Models
For a list of pretrained models, see [Hugging Face docs](https://huggingface.co/pytorch-transformers/pretrained_models.html).
The `model_types` available for each task can be found under their respective section. Any pretrained model of that type
found in the Hugging Face docs should work. To use any of them set the correct `model_type` and `model_name` in the `args`
%package help
Summary: Development documents and examples for simpletransformers
Provides: python3-simpletransformers-doc
%description help
## Current Pretrained Models
For a list of pretrained models, see [Hugging Face docs](https://huggingface.co/pytorch-transformers/pretrained_models.html).
The `model_types` available for each task can be found under their respective section. Any pretrained model of that type
found in the Hugging Face docs should work. To use any of them set the correct `model_type` and `model_name` in the `args`
%prep
%autosetup -n simpletransformers-0.63.9
%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-simpletransformers -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Sun Apr 23 2023 Python_Bot <Python_Bot@openeuler.org> - 0.63.9-1
- Package Spec generated
|
