This release is a pre-release and may not be stable for production use.
BigDL Nano automatically accelerates TensorFlow and PyTorch pipelines by applying modern CPU optimizations.
See here for more information.
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2 maintainers
Release files for bigdl-nano 2.4.0b20230508
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Built distributions (wheels)
| File | Actions Reset | |||
|---|---|---|---|---|
| bigdl_nano-2.4.0b20230508-py3-none-win_amd64.whl | Python 3 | none | Windows x86-64 | Details for bigdl_nano-2.4.0b20230508-py3-none-win_amd64.whl |
| bigdl_nano-2.4.0b20230508-py3-none-manylinux2010_x86_64.whl | Python 3 | none | Linux glibc 2.12+ x86-64 | Details for bigdl_nano-2.4.0b20230508-py3-none-manylinux2010_x86_64.whl |
| bigdl_nano-2.4.0b20230508-py3-none-macosx_11_0_arm64.whl | Python 3 | none | macOS 11.0+ ARM64 | Details for bigdl_nano-2.4.0b20230508-py3-none-macosx_11_0_arm64.whl |
| bigdl_nano-2.4.0b20230508-py3-none-macosx_10_11_x86_64.whl | Python 3 | none | macOS 10.11+ x86-64 | Details for bigdl_nano-2.4.0b20230508-py3-none-macosx_10_11_x86_64.whl |
Total release size: 10.9 MB
Release files / bigdl_nano-2.4.0b20230508-py3-none-win_amd64.whl
| Download URL | bigdl_nano-2.4.0b20230508-py3-none-win_amd64.whl |
|---|---|
| Size | 2.7 MB |
| Tags | Python 3 Windows x86-64 |
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No |
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twine/4.0.1 CPython/3.7.15
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Release files / bigdl_nano-2.4.0b20230508-py3-none-manylinux2010_x86_64.whl
| Download URL | bigdl_nano-2.4.0b20230508-py3-none-manylinux2010_x86_64.whl |
|---|---|
| Size | 2.7 MB |
| Tags | Linux glibc 2.12+ x86-64 Python 3 |
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twine/4.0.1 CPython/3.7.15
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Release files / bigdl_nano-2.4.0b20230508-py3-none-macosx_11_0_arm64.whl
| Download URL | bigdl_nano-2.4.0b20230508-py3-none-macosx_11_0_arm64.whl |
|---|---|
| Size | 2.7 MB |
| Tags | Python 3 macOS 11.0+ ARM64 |
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No |
| Uploaded via |
twine/4.0.1 CPython/3.7.15
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Release files / bigdl_nano-2.4.0b20230508-py3-none-macosx_10_11_x86_64.whl
| Download URL | bigdl_nano-2.4.0b20230508-py3-none-macosx_10_11_x86_64.whl |
|---|---|
| Size | 2.7 MB |
| Tags | Python 3 macOS 10.11+ x86-64 |
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SHA-256 checksum How to use checksums |
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| Uploaded via |
twine/4.0.1 CPython/3.7.15
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