fairseq2n

FAIR Sequence Modeling Toolkit (Native)

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https://github.com/facebookresearch/fairseq2

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This version

0.2.1

Apr 2, 2024

0.2.0

Nov 29, 2023

0.1.1

Sep 7, 2023

0.1.0

Aug 22, 2023

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fairseq2n-0.2.1-cp311-cp311-manylinux2014_x86_64.whl (2.3 MB view hashes)

Uploaded Apr 2, 2024 CPython 3.11

fairseq2n-0.2.1-cp311-cp311-macosx_14_0_arm64.whl (1.8 MB view hashes)

Uploaded Apr 2, 2024 CPython 3.11 macOS 14.0+ ARM64

fairseq2n-0.2.1-cp310-cp310-manylinux2014_x86_64.whl (2.3 MB view hashes)

Uploaded Apr 2, 2024 CPython 3.10

fairseq2n-0.2.1-cp310-cp310-macosx_14_0_arm64.whl (1.8 MB view hashes)

Uploaded Apr 2, 2024 CPython 3.10 macOS 14.0+ ARM64

fairseq2n-0.2.1-cp39-cp39-manylinux2014_x86_64.whl (2.3 MB view hashes)

Uploaded Apr 2, 2024 CPython 3.9

fairseq2n-0.2.1-cp39-cp39-macosx_14_0_arm64.whl (1.8 MB view hashes)

Uploaded Apr 2, 2024 CPython 3.9 macOS 14.0+ ARM64

fairseq2n-0.2.1-cp38-cp38-manylinux2014_x86_64.whl (2.3 MB view hashes)

Uploaded Apr 2, 2024 CPython 3.8

fairseq2n-0.2.1-cp38-cp38-macosx_14_0_arm64.whl (1.8 MB view hashes)

Uploaded Apr 2, 2024 CPython 3.8 macOS 14.0+ ARM64

Hashes for fairseq2n-0.2.1-cp311-cp311-manylinux2014_x86_64.whl

Hashes for fairseq2n-0.2.1-cp311-cp311-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`6da939c8f53ef4cfe35ae73a0a029697aa3f46c6ece0fc368ef1a9ea2a166d13`
MD5	`15e6aa671b38b4b1dcff8d0b85cf3b5f`
BLAKE2b-256	`021efe4d67b2852d28b961eceedfd52ac3bcebe64b70cc736f0c9b985adee588`

Hashes for fairseq2n-0.2.1-cp311-cp311-macosx_14_0_arm64.whl

Hashes for fairseq2n-0.2.1-cp311-cp311-macosx_14_0_arm64.whl
Algorithm	Hash digest
SHA256	`eaef99962b3b61c16238af31c285a1aaade35664c395076eff8e9d171e7e3cc7`
MD5	`0118c36e67f58c4683faae1d52ef2092`
BLAKE2b-256	`74442b34c0ec4308a315b97ee1ff832239e7c992143cb523fa238dad02793d89`

Hashes for fairseq2n-0.2.1-cp310-cp310-manylinux2014_x86_64.whl

Hashes for fairseq2n-0.2.1-cp310-cp310-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`e37c68a3c7880a5344c3c458999681e69bb6c2f98c22d11c1e059cc9b5c4fa57`
MD5	`7bc26954099b06d6c7879ba77c23e00b`
BLAKE2b-256	`6f2fcfbda23dd78c0c7f7c96129402cf9992e2c48b3fd15a544fa6c7262d611c`

Hashes for fairseq2n-0.2.1-cp310-cp310-macosx_14_0_arm64.whl

Hashes for fairseq2n-0.2.1-cp310-cp310-macosx_14_0_arm64.whl
Algorithm	Hash digest
SHA256	`0cc49ab97953530c761d13f5cfe5f51f8c9f21d7fd7e492fc0e95f4f370b6b46`
MD5	`0a74683e949caa2580f85804cdc51135`
BLAKE2b-256	`69deda8554b2af5e8e5cfbf3c0c6e308e660c567e4f302e531176cfc339ec5f5`

Hashes for fairseq2n-0.2.1-cp39-cp39-manylinux2014_x86_64.whl

Hashes for fairseq2n-0.2.1-cp39-cp39-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`bba3fe4baf23a337902872db88bf513c014fcb4c3d3015a57a133bce1c212cb4`
MD5	`95909dd56f102ec9480a8f26a09d57b3`
BLAKE2b-256	`aaf9b10cd3ed2ae210c145163b95eef4805a9ea230164f6d64c4d65925698518`

Hashes for fairseq2n-0.2.1-cp39-cp39-macosx_14_0_arm64.whl

Hashes for fairseq2n-0.2.1-cp39-cp39-macosx_14_0_arm64.whl
Algorithm	Hash digest
SHA256	`82f5dac746f169eae4beafeb7a5600a800c76b4467b303a57c05ae6589e35154`
MD5	`9b85f3d1f2c96692263a0ad3a8b60401`
BLAKE2b-256	`f480a76136efb754dca3777fa6e9d9ca10ecbe74cf21655b8ae66a864738a569`

Hashes for fairseq2n-0.2.1-cp38-cp38-manylinux2014_x86_64.whl

Hashes for fairseq2n-0.2.1-cp38-cp38-manylinux2014_x86_64.whl
Algorithm	Hash digest
SHA256	`21406096418411dc506e9ca9d4bc52170c9cdffbc8454254f95f0c3c3322c5ba`
MD5	`3886dad70964b2ac8a19c3a9dc69baab`
BLAKE2b-256	`087767a4e83ef103f7f59ffb07eac1e5184eeeaec1001f64f0dd33773da2be4b`

Hashes for fairseq2n-0.2.1-cp38-cp38-macosx_14_0_arm64.whl

Hashes for fairseq2n-0.2.1-cp38-cp38-macosx_14_0_arm64.whl
Algorithm	Hash digest
SHA256	`79c3d905b0d6882b7990cdefd6b4e04e066e784adef268244539bdbfb4e43a79`
MD5	`9b34d5569bdad8d96fab219894a5c8d4`
BLAKE2b-256	`71e529395b9f6c66614272b0ec520ba578cf1e680f0066926f52de7f8afd1d71`