gcld3

CLD3 is a neural network model for language identification.

Project description

CLD3 is a neural network model for language identification. This package contains the inference code and a trained model. See https://github.com/google/cld3 for more details.

Project details

Release history Release notifications | RSS feed

This version

3.0.13

Aug 19, 2020

3.0.1

Jul 25, 2020

Download files

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

Source Distribution

gcld3-3.0.13.tar.gz (647.8 kB view hashes)

Uploaded Aug 19, 2020 Source

Built Distributions

gcld3-3.0.13-pp36-pypy36_pp73-manylinux2010_x86_64.whl (960.6 kB view hashes)

Uploaded Aug 19, 2020 PyPy manylinux: glibc 2.12+ x86-64

gcld3-3.0.13-pp36-pypy36_pp73-macosx_10_9_x86_64.whl (1.3 MB view hashes)

Uploaded Aug 19, 2020 PyPy macOS 10.9+ x86-64

gcld3-3.0.13-cp38-cp38-manylinux2010_x86_64.whl (3.8 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.8 manylinux: glibc 2.12+ x86-64

gcld3-3.0.13-cp38-cp38-macosx_10_9_x86_64.whl (1.3 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.8 macOS 10.9+ x86-64

gcld3-3.0.13-cp36-cp36m-manylinux2010_x86_64.whl (3.8 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.6m manylinux: glibc 2.12+ x86-64

gcld3-3.0.13-cp36-cp36m-macosx_10_9_x86_64.whl (1.3 MB view hashes)

Uploaded Aug 19, 2020 CPython 3.6m macOS 10.9+ x86-64

Hashes for gcld3-3.0.13.tar.gz

Hashes for gcld3-3.0.13.tar.gz
Algorithm	Hash digest
SHA256	`47c8c779bfe7372a38564b0cd357556dc362aec81cb55b0c889059e8b952e959`
MD5	`a70d9add709abfc96fe77cfeb9c64560`
BLAKE2b-256	`3a7372e469743a7e299e9a074857f7cac9f2b045bd495e20fdbd75cf081277c3`

Hashes for gcld3-3.0.13-pp36-pypy36_pp73-manylinux2010_x86_64.whl

Hashes for gcld3-3.0.13-pp36-pypy36_pp73-manylinux2010_x86_64.whl
Algorithm	Hash digest
SHA256	`4fc4ae1c8c7baab21a46fc66074787d010ca338f5c4b2ff80dd2448d18cc3d89`
MD5	`6594ad0128f437086249260d40f39125`
BLAKE2b-256	`575e0470b54e39ef65a60289ff92d50f252bab3c021c254f57ef1b730548fd46`

Hashes for gcld3-3.0.13-pp36-pypy36_pp73-macosx_10_9_x86_64.whl

Hashes for gcld3-3.0.13-pp36-pypy36_pp73-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`b56a9852861c7209434917885b8331ddf5f11d3d5810baafb9a29ffd5ccd35d1`
MD5	`da2ce7d7428227006ec0a055cda9cb90`
BLAKE2b-256	`94a40ca7f3537eb0f5588bf55f0c2048dc1e32ef4ba1b8b66f12ca71d1746557`

Hashes for gcld3-3.0.13-cp38-cp38-manylinux2010_x86_64.whl

Hashes for gcld3-3.0.13-cp38-cp38-manylinux2010_x86_64.whl
Algorithm	Hash digest
SHA256	`c6bc0ecf3d95943a2b9fe61214aab8284a3b33f25e07c6caad064ea59417620f`
MD5	`8773c77acf2e61c6b593654bd015550a`
BLAKE2b-256	`406b3a034b64304f2829636c34720fe8cfa62b835ff6f6a0718fbb313bd7bae1`

Hashes for gcld3-3.0.13-cp38-cp38-macosx_10_9_x86_64.whl

Hashes for gcld3-3.0.13-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`fb745958278bfcc230fe3e15af3babb2752e77afd929ae0f95b9ef52648f3271`
MD5	`2164c32d9cd63a91dd63bfebe4d55879`
BLAKE2b-256	`d76b3e5c3110e35e624d5d58b02e3d878c2dcc6e92307f085a2cea59f450b080`

Hashes for gcld3-3.0.13-cp36-cp36m-manylinux2010_x86_64.whl

Hashes for gcld3-3.0.13-cp36-cp36m-manylinux2010_x86_64.whl
Algorithm	Hash digest
SHA256	`51538b26dd1741f49ceb03421710d4355c6ce3fd257a2ddebe868e36458f5d45`
MD5	`1a22da823c1aac8ec69b9524d7f1a696`
BLAKE2b-256	`61630f5816f6c60fce2f5b2d6106ad1d3a50fc785ac68b1520a78c80b4b84fb7`

Hashes for gcld3-3.0.13-cp36-cp36m-macosx_10_9_x86_64.whl

Hashes for gcld3-3.0.13-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm	Hash digest
SHA256	`11a127e493c2952a83a957e2f025d6ff8b1d2efd353baa25bd99d7ceb3c96c54`
MD5	`d5c9eab0a3eb33409f35800f0624d4e8`
BLAKE2b-256	`82a115da08b18fa95bf886a26dd757f279ab786c13fc32f7eada74dba30bb149`