Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

TensorFlow Recommenders Addons are a collection of projects related to large-scale recommendation systems built upon TensorFlow. They are contributed and maintained by the community. Those contributions will be complementary to TensorFlow Core and TensorFlow Recommenders etc.

Metadata

Release files for tfra-nightly 0.5.0.dev20230314095048

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for tfra-nightly 0.5.0.dev20230314095048
File
tfra_nightly-0.5.0.dev20230314095048-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl CPython 3.9 CPython 3.9 Linux glibc 2.12+ x86-64 Details
tfra_nightly-0.5.0.dev20230314095048-cp39-cp39-macosx_10_13_x86_64.whl CPython 3.9 CPython 3.9 macOS 10.13+ x86-64 Details
tfra_nightly-0.5.0.dev20230314095048-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl CPython 3.8 CPython 3.8 Linux glibc 2.12+ x86-64 Details
tfra_nightly-0.5.0.dev20230314095048-cp38-cp38-macosx_10_13_x86_64.whl CPython 3.8 CPython 3.8 macOS 10.13+ x86-64 Details
tfra_nightly-0.5.0.dev20230314095048-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64 Details
tfra_nightly-0.5.0.dev20230314095048-cp37-cp37m-macosx_10_13_x86_64.whl CPython 3.7 CPython 3.7 pymalloc macOS 10.13+ x86-64 Details

Total release size: 32.2 MB

Release files / tfra_nightly-0.5.0.dev20230314095048-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Download URL tfra_nightly-0.5.0.dev20230314095048-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Size 6.6 MB
Tags CPython 3.9 Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
da4932515942166e4979de2fd397e42e31ccf4c5563007868609c0a76eaffce2
BLAKE2b-256 checksum
How to use checksums
4ef5a93edbcd04a5134e47f1b4ab6f836500a9b9e7bbee445cf542f6e23398a0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.16

Release files / tfra_nightly-0.5.0.dev20230314095048-cp39-cp39-macosx_10_13_x86_64.whl

Download URL tfra_nightly-0.5.0.dev20230314095048-cp39-cp39-macosx_10_13_x86_64.whl
Size 4.1 MB
Tags CPython 3.9 macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
8ae7184461fab1e818997b846937581588e5219a1ea5303ee9fa8005b9b31da0
BLAKE2b-256 checksum
How to use checksums
6fafdb89a11327989cc236c266f14e4f087e2e5ea377d4ca3f3fabcf25925663
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.16

Release files / tfra_nightly-0.5.0.dev20230314095048-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Download URL tfra_nightly-0.5.0.dev20230314095048-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Size 6.6 MB
Tags CPython 3.8 Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
4627f702024752447ef5537e27e7021418c57e44c3ee3faae2d26f28ae8974dd
BLAKE2b-256 checksum
How to use checksums
c8e32f0971c8da5d370e94a54e89b7aba13341c438e22fea32ec5c70ebcb4204
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.16

Release files / tfra_nightly-0.5.0.dev20230314095048-cp38-cp38-macosx_10_13_x86_64.whl

Download URL tfra_nightly-0.5.0.dev20230314095048-cp38-cp38-macosx_10_13_x86_64.whl
Size 4.1 MB
Tags CPython 3.8 macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
9347aefe10cff8435ed64d41b61af719d58eb293fc83111cf670f6bded15c75a
BLAKE2b-256 checksum
How to use checksums
00037756e1482ee7095751f45b8a18e2e124699070e73c220dc0a967caf6c7b1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.16

Release files / tfra_nightly-0.5.0.dev20230314095048-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl

Download URL tfra_nightly-0.5.0.dev20230314095048-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Size 6.6 MB
Tags CPython 3.7 CPython 3.7 pymalloc Linux glibc 2.12+ x86-64
SHA-256 checksum
How to use checksums
65aa2afde64bee4e131093c118d0aba9877efc9be4ffeef206860dbd1ac922c6
BLAKE2b-256 checksum
How to use checksums
a929d1bf33d852345c91dd4cfd7f2c3899016ef21d8e4c4b367d80cbaa9ede14
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.16

Release files / tfra_nightly-0.5.0.dev20230314095048-cp37-cp37m-macosx_10_13_x86_64.whl

Download URL tfra_nightly-0.5.0.dev20230314095048-cp37-cp37m-macosx_10_13_x86_64.whl
Size 4.1 MB
Tags CPython 3.7 CPython 3.7 pymalloc macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
823a100add35bddf1dc02b7acb7a1681e1ea5ebcebb9bae4a57c320a57a968b2
BLAKE2b-256 checksum
How to use checksums
22afcf442ba36fbc60dd30f48c80e3b9e343886a4a753c0160a8f155a223aa7f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.16

Security for tfra-nightly 0.5.0.dev20230314095048

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page