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authorCoprDistGit <infra@openeuler.org>2024-01-27 17:38:06 +0000
committerCoprDistGit <infra@openeuler.org>2024-01-27 17:38:06 +0000
commitf325548e3e82d3a5c0b95ddd0f39905d72828f72 (patch)
tree75e17934972daf5f71f8b31e15563e1462218a58
parent577e84a25df87420e7d10f4206a55983b3354b89 (diff)
automatic import of python-transformersopeneuler22.03_LTS_SP2
-rw-r--r--.gitignore1
-rw-r--r--python-transformers.spec59
-rw-r--r--sources1
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diff --git a/.gitignore b/.gitignore
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+/python-transformers-4.37.1.tar.gz
diff --git a/python-transformers.spec b/python-transformers.spec
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+%global _empty_manifest_terminate_build 0
+Name: python-transformers
+Version: 4.37.1
+Release: 1
+Summary: HuggingFace Transformers package for python3
+License: Apache-2.0
+URL: https://huggingface.co/docs/transformers/index
+Source0: https://github.com/huggingface/transformers/archive/refs/tags/v%{version}.tar.gz#/%{name}-%{version}.tar.gz
+
+Requires: python3-filelock
+Requires: python3-packaging
+Requires: python3-numpy
+Requires: python3-pyyaml
+Requires: python3-regex
+Requires: python3-requests
+Requires: python3-safetensors >= 0.3.1
+Requires: python3-tqdm
+
+%description
+Transformers support framework interoperability between PyTorch, TensorFlow, and JAX. This provides the flexibility to use a different framework at each stage of a model’s life; train a model in three lines of code in one framework, and load it for inference in another. Models can also be exported to a format like ONNX and TorchScript for deployment in production environments.
+
+%package -n python3-transformers
+Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration
+Provides: python-transformer
+BuildRequires: python3-devel
+BuildRequires: python3-setuptools
+#BuildRequires: python3-setuptools_scm
+BuildRequires: python3-pip
+BuildRequires: python3-wheel
+BuildRequires: python3-hatchling
+
+%description -n python3-transformers
+Transformers provides APIs and tools to easily download and train state-of-the-art pretrained models. Using pretrained models can reduce your compute costs, carbon footprint, and save you the time and resources required to train a model from scratch. These models support common tasks in different modalities, such as natural language processing, computer vision, audio and multimodal.
+
+%package help
+Summary: Development documents and examples for torch
+Provides: python3-transformers-doc
+%description help
+description for python3 transformers documents
+
+%prep
+%autosetup -p1 -n transformers-%{version}
+
+%build
+%pyproject_build
+
+%install
+%pyproject_install
+
+%files -n python3-transformers
+%doc *.md
+%license LICENSE
+%{_bindir}/transformers-cli
+%{python3_sitelib}/transformers/*
+%{python3_sitelib}/transformers-%{version}.dist-info/*
+
+%changelog
+* Fri Jan 26 2024 menma <1316818279@qq.com> - 0.2.1-1
+- Package init
diff --git a/sources b/sources
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index 0000000..002d2b1
--- /dev/null
+++ b/sources
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+800c474105508eeb7adc3b285eab3fc6 python-transformers-4.37.1.tar.gz