The author of this package has not provided a project description

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for lucidrains from gravatar.com lucidrains

Credits

Author: Phil Wang

License

MIT License (MIT)

Tags

artificial intelligence deep learning attention-mechanism

Classifiers

Report project as malware

Metadata

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for lucidrains from gravatar.com lucidrains

Credits

Author: Phil Wang

License

MIT License (MIT)

Tags

artificial intelligence deep learning attention-mechanism

Classifiers

Report project as malware

Release files for memory-efficient-attention-pytorch 0.1.6

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

Source distribution (sdist)

Source distribution for memory-efficient-attention-pytorch 0.1.6
File Size Uploaded
memory-efficient-attention-pytorch-0.1.6.tar.gz 11.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for memory-efficient-attention-pytorch 0.1.6
File Interpreter ABI Platform
memory_efficient_attention_pytorch-0.1.6-py3-none-any.whl 15.0 kB Python 3 none any Details

Total release size: 26.3 kB

Release files / memory-efficient-attention-pytorch-0.1.6.tar.gz

Download URL memory-efficient-attention-pytorch-0.1.6.tar.gz
Size 11.3 kB
Tags Source
SHA-256 checksum
How to use checksums 		8aaaebb095c40b6c3e18359d2f4978c95984eb77b467ac58baa503bdb92914bf
BLAKE2b-256 checksum
How to use checksums 		6f6af263c5c5b82d9c2bfb278fae9d6bcd57aab1b3870eb901fbc8e261b83cdb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing? 		No
Uploaded via twine/4.0.2 CPython/3.9.17

Release files / memory_efficient_attention_pytorch-0.1.6-py3-none-any.whl

Download URL memory_efficient_attention_pytorch-0.1.6-py3-none-any.whl
Size 15.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums 		efbb2676f8695b21a29d96d83f84818be257a35ac4c89f94d7d93f59819d38ed
BLAKE2b-256 checksum
How to use checksums 		ee77482a6a9abcc4b2493f5fa077b05d38c1a384643c22cd42cbdc751d3c4961
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing? 		No
Uploaded via twine/4.0.2 CPython/3.9.17

Release history Release notifications | RSS feed

This release

0.1.6 This release

2 release files

0.1.5

2 release files

0.1.4

2 release files

0.1.2

2 release files

0.1.1

2 release files

0.1.0

2 release files

0.0.27

2 release files

0.0.26

2 release files

0.0.25

2 release files

0.0.24

2 release files

0.0.23

2 release files

0.0.22

2 release files

0.0.21

2 release files

0.0.20

2 release files

0.0.19

2 release files

0.0.18

2 release files

0.0.17

2 release files

0.0.16

2 release files

0.0.15

2 release files

0.0.14

2 release files

0.0.12

2 release files

0.0.11

2 release files

0.0.10

2 release files

0.0.9

2 release files

0.0.8

2 release files

0.0.7

2 release files

0.0.6

2 release files

0.0.5

2 release files

0.0.4

2 release files

0.0.2

2 release files

0.0.1

2 release files

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