Skip to main content

TensorFlow Recommenders Addons.

Project description

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.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

tfra_nightly-0.3.0.dev20211012115405-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (6.0 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.12+ x86-64

tfra_nightly-0.3.0.dev20211012115405-cp39-cp39-macosx_10_13_x86_64.whl (3.8 MB view details)

Uploaded CPython 3.9 macOS 10.13+ x86-64

tfra_nightly-0.3.0.dev20211012115405-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (6.0 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.12+ x86-64

tfra_nightly-0.3.0.dev20211012115405-cp38-cp38-macosx_10_13_x86_64.whl (3.8 MB view details)

Uploaded CPython 3.8 macOS 10.13+ x86-64

tfra_nightly-0.3.0.dev20211012115405-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (6.0 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.12+ x86-64

tfra_nightly-0.3.0.dev20211012115405-cp37-cp37m-macosx_10_13_x86_64.whl (3.8 MB view details)

Uploaded CPython 3.7m macOS 10.13+ x86-64

tfra_nightly-0.3.0.dev20211012115405-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (6.0 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.12+ x86-64

tfra_nightly-0.3.0.dev20211012115405-cp36-cp36m-macosx_10_13_x86_64.whl (3.8 MB view details)

Uploaded CPython 3.6m macOS 10.13+ x86-64

File details

Details for the file tfra_nightly-0.3.0.dev20211012115405-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfra_nightly-0.3.0.dev20211012115405-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 ba16b64f75ba30043f4016386037e2eb49ab4f4cf0aff2d46b3dbcbaee4da17a
MD5 be74541147bc7cd54b4b139a61669bc1
BLAKE2b-256 b497c9f9f02c7dd93cec6def8ece7fe3ee6900705069b44e916eb27a26b2de53

See more details on using hashes here.

File details

Details for the file tfra_nightly-0.3.0.dev20211012115405-cp39-cp39-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfra_nightly-0.3.0.dev20211012115405-cp39-cp39-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 6a7054ba8947cd372d4037691599c6b8d1b50e44ad370cf45072d92c00b0364b
MD5 ef3166618082276d218f21f09d924dde
BLAKE2b-256 68f9752cb997abf123ca76c362391ea5062432bcc3b46629fb38b4b8fe39bfe6

See more details on using hashes here.

File details

Details for the file tfra_nightly-0.3.0.dev20211012115405-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfra_nightly-0.3.0.dev20211012115405-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 572ada5186a50166db23c09eed644871bb6998570df91bd380bfe7e23d745906
MD5 0204fd21ece86ebcf548de5dd83badc9
BLAKE2b-256 ce658c88563f121aa8c3df8711a0ebfae424fb67eacd503c8c6c3151e85628be

See more details on using hashes here.

File details

Details for the file tfra_nightly-0.3.0.dev20211012115405-cp38-cp38-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfra_nightly-0.3.0.dev20211012115405-cp38-cp38-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 e4504b41fbef4f6af7affda0670bf01323179fb9ad658404cd6ed80a5d4e209f
MD5 dc5414d391f1197a3cbf5cd6cdc40741
BLAKE2b-256 b77fda8e00a44c179549f3ad5e79e196018f473702dc9a0b174f422b850aea76

See more details on using hashes here.

File details

Details for the file tfra_nightly-0.3.0.dev20211012115405-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfra_nightly-0.3.0.dev20211012115405-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 3722ec4bae01817570f80c1d5e89cf536bf80b4fae09333d433af9ee8f75f433
MD5 6b5b28d31e6a9b15bb553c384a5f88c8
BLAKE2b-256 124166512a385dee5395ad17439b70d279edfc0f174d0e8f8431d707b5ac8626

See more details on using hashes here.

File details

Details for the file tfra_nightly-0.3.0.dev20211012115405-cp37-cp37m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfra_nightly-0.3.0.dev20211012115405-cp37-cp37m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 0bcac3a51d344d5cdae8ec70a717ee28d6f02de558e04f87adf8e8aca913a3fb
MD5 5f43dadd629424bd7c5687ff53bf0663
BLAKE2b-256 670e078ac9cf13b0093e315496ffdf57a4db5e9da04c1099174ec0f6e6e08c80

See more details on using hashes here.

File details

Details for the file tfra_nightly-0.3.0.dev20211012115405-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for tfra_nightly-0.3.0.dev20211012115405-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 3102e56464d6329488273646adf30b05457f187ef7da2a58b3c6cb9a4536f6d6
MD5 05a9386f09763536830717d96e988990
BLAKE2b-256 722b6cecca08d87756346a316e38b54076efc67def61da6dea8d0903720c424a

See more details on using hashes here.

File details

Details for the file tfra_nightly-0.3.0.dev20211012115405-cp36-cp36m-macosx_10_13_x86_64.whl.

File metadata

File hashes

Hashes for tfra_nightly-0.3.0.dev20211012115405-cp36-cp36m-macosx_10_13_x86_64.whl
Algorithm Hash digest
SHA256 6626207fb718ee56920b2fbe5fedcc1a50724556cbaeb6b8d850685995146fe1
MD5 b760895850161767978ac90191989c27
BLAKE2b-256 f5a14d2374d2834b9dfceba9fd513e2574faaf0db483a77a6782e5a4d53f0cb6

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page