Block Recurrent Transformer - Pytorch

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for lucidrains from gravatar.com lucidrains

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Phil Wang
  • Tags artificial intelligence, deep learning, transformers, attention mechanism, recurrence
Classifiers

Project description

The author of this package has not provided a project description

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for lucidrains from gravatar.com lucidrains

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Phil Wang
  • Tags artificial intelligence, deep learning, transformers, attention mechanism, recurrence
Classifiers

Release history Release notifications | RSS feed

0.4.4

0.4.3

0.4.2

0.4.1

0.4.0

0.3.3

0.3.2

0.3.1

This version

0.3.0

0.2.2

0.2.1

0.2.0

0.1.4

0.1.2

0.1.1

0.1.0

0.0.19

0.0.18

0.0.17

0.0.16

0.0.15

0.0.14

0.0.12

0.0.11

0.0.10

0.0.9

0.0.7

0.0.6

0.0.5

0.0.4

0.0.3

0.0.2

0.0.1

Download files

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

Source Distribution

block-recurrent-transformer-pytorch-0.3.0.tar.gz (12.0 kB view details)

Uploaded Source

Built Distribution

block_recurrent_transformer_pytorch-0.3.0-py3-none-any.whl (10.6 kB view details)

Uploaded Python 3

File details

Details for the file block-recurrent-transformer-pytorch-0.3.0.tar.gz.

File metadata

File hashes

Hashes for block-recurrent-transformer-pytorch-0.3.0.tar.gz
Algorithm Hash digest
SHA256 1744d42b3df3c02b9e567274e8e33f7099a5d9bebf4dd89becfcd2f20e5b6238
MD5 2e3f38142d922f36e095815d48b9391e
BLAKE2b-256 e85a52bcade02c5831d7b129e638c5e80bc2b021c8a47fd59ef20e174f6b5a61

See more details on using hashes here.

File details

Details for the file block_recurrent_transformer_pytorch-0.3.0-py3-none-any.whl.

File metadata

File hashes

Hashes for block_recurrent_transformer_pytorch-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 8262ca06b8b578c374564e068b781d49cd2abc0b2706bd1587d0c99c91cf58ad
MD5 b6f8db9bfa6f9c373b150cffc110e654
BLAKE2b-256 10e6fa70f82439a093d37892bb9f02d7e9490d3dcfcbcb850891e73aee914102

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