Package: python3-thinc (9.0.0-2 and others)

[ Source: python-thinc  ]

Practical Machine Learning for NLP in Python

Thinc is the machine learning library powering spaCy <https://spacy.io>. It features a battle-tested linear model designed for large sparse learning problems, and a flexible neural network model under development for spaCy v2.0 <https://spacy.io/usage/v2>.

Thinc is a practical toolkit for implementing models that follow the "Embed, encode, attend, predict" architecture. It's designed to be easy to install, efficient for CPU usage and optimised for NLP and deep learning with text – in particular, hierarchically structured input and variable-length sequences.

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Download python3-thinc

Download for all available architectures

Architecture	Version	Package Size	Installed Size	Files
alpha (unofficial port)	6.12.1-1	966.8 kB	13,146.0 kB	[list of files]
amd64	9.0.0-2	519.0 kB	2,963.0 kB	[list of files]
arm64	9.0.0-2	469.6 kB	2,914.0 kB	[list of files]
armhf	9.0.0-2	478.8 kB	2,452.0 kB	[list of files]
hppa (unofficial port)	9.0.0-2	485.4 kB	3,224.0 kB	[list of files]
i386	9.0.0-2	509.8 kB	3,017.0 kB	[list of files]
ia64 (unofficial port)	8.2.2-1	906.1 kB	7,485.0 kB	[list of files]
m68k (unofficial port)	9.0.0-2	465.9 kB	2,796.0 kB	[list of files]
mips64el	9.0.0-2	443.6 kB	3,070.0 kB	[list of files]
ppc64 (unofficial port)	9.0.0-2	483.3 kB	3,297.0 kB	[list of files]
riscv64	9.0.0-2	508.1 kB	2,616.0 kB	[list of files]
s390x	9.0.0-2	494.1 kB	2,960.0 kB	[list of files]
sh4 (unofficial port)	6.12.1-1	1,083.4 kB	12,038.0 kB	[list of files]
sparc64 (unofficial port)	9.0.0-2	443.3 kB	5,748.0 kB	[list of files]
x32 (unofficial port)	6.12.1-1	886.9 kB	10,679.0 kB	[list of files]