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 0.6.1.dev20240529030102

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 0.6.1.dev20240529030102
File
tfra_nightly-0.6.1.dev20240529030102-cp311-cp311-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.11 CPython 3.11 Linux glibc 2.12+ x86-64, Linux glibc 2.17+ x86-64 Details
tfra_nightly-0.6.1.dev20240529030102-cp311-cp311-macosx_10_13_x86_64.whl CPython 3.11 CPython 3.11 macOS 10.13+ x86-64 Details
tfra_nightly-0.6.1.dev20240529030102-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.10 CPython 3.10 Linux glibc 2.17+ x86-64, Linux glibc 2.12+ x86-64 Details
tfra_nightly-0.6.1.dev20240529030102-cp310-cp310-macosx_10_13_x86_64.whl CPython 3.10 CPython 3.10 macOS 10.13+ x86-64 Details
tfra_nightly-0.6.1.dev20240529030102-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl CPython 3.9 CPython 3.9 Linux glibc 2.17+ x86-64, Linux glibc 2.12+ x86-64 Details
tfra_nightly-0.6.1.dev20240529030102-cp39-cp39-macosx_10_13_x86_64.whl CPython 3.9 CPython 3.9 macOS 10.13+ x86-64 Details

Total release size: 32.4 MB

Release files / tfra_nightly-0.6.1.dev20240529030102-cp311-cp311-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfra_nightly-0.6.1.dev20240529030102-cp311-cp311-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size 6.6 MB
Tags CPython 3.11 Linux glibc 2.12+ x86-64 Linux glibc 2.17+ x86-64
SHA-256 checksum
How to use checksums
271020737c31ecffae6040c513a040fe7129306bbd7b5262999e7075ae3ef7d9
BLAKE2b-256 checksum
How to use checksums
c2a9460e8cac74f73f48fd10660ebb0005247075adaf27027ecc972dfce8336f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.17

Release files / tfra_nightly-0.6.1.dev20240529030102-cp311-cp311-macosx_10_13_x86_64.whl

Download URL tfra_nightly-0.6.1.dev20240529030102-cp311-cp311-macosx_10_13_x86_64.whl
Size 4.2 MB
Tags CPython 3.11 macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
69ed9f80c27ecf8d6cd1bae9f0654e87a323c274867b893d17d14e9beb6f4500
BLAKE2b-256 checksum
How to use checksums
0ad4570e1b661dc373dcec1d7d9e0b04a31935a6067c44e7c5d300d9c54ba525
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.17

Release files / tfra_nightly-0.6.1.dev20240529030102-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfra_nightly-0.6.1.dev20240529030102-cp310-cp310-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size 6.6 MB
Tags CPython 3.10 Linux glibc 2.12+ x86-64 Linux glibc 2.17+ x86-64
SHA-256 checksum
How to use checksums
066d3f61d7122c90b5bced7010e8a5f55a6f7182852fd2b296f1ea46cb56079f
BLAKE2b-256 checksum
How to use checksums
154ca61401c6769c29366120d2b92975adc94756dcfc5f66c6569f98c4af30f0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.17

Release files / tfra_nightly-0.6.1.dev20240529030102-cp310-cp310-macosx_10_13_x86_64.whl

Download URL tfra_nightly-0.6.1.dev20240529030102-cp310-cp310-macosx_10_13_x86_64.whl
Size 4.2 MB
Tags CPython 3.10 macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
5d6fcd59fd3c8afba81e898897dbea02b4a528de5b2b8c3e67b95cb748141112
BLAKE2b-256 checksum
How to use checksums
67a7638c8f02f260e1131b179f0bf01feb61a8959cca583c466580acfb289d0f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.17

Release files / tfra_nightly-0.6.1.dev20240529030102-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Download URL tfra_nightly-0.6.1.dev20240529030102-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Size 6.6 MB
Tags CPython 3.9 Linux glibc 2.12+ x86-64 Linux glibc 2.17+ x86-64
SHA-256 checksum
How to use checksums
2a67284ccf2402b2d4cd0fcd17f5b247d0a5e8d2ccdb4e67164e10e50af203e4
BLAKE2b-256 checksum
How to use checksums
e049de673d0f9d3e10fb8b5bf3c3919987f872b25fbc63aed8e116b5acf73758
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.17

Release files / tfra_nightly-0.6.1.dev20240529030102-cp39-cp39-macosx_10_13_x86_64.whl

Download URL tfra_nightly-0.6.1.dev20240529030102-cp39-cp39-macosx_10_13_x86_64.whl
Size 4.2 MB
Tags CPython 3.9 macOS 10.13+ x86-64
SHA-256 checksum
How to use checksums
06b25b2406268561128002af58926b2c5cf39192b4b0a3414f476e7ac6e5e870
BLAKE2b-256 checksum
How to use checksums
aae1d6cc1b5e82fc05edb5034272aa803ca8ddb6aa3ee5fa7eafbf4a07806289
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.7.17

Security for tfra-nightly 0.6.1.dev20240529030102

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