How to Install and Uninstall python3-thinc Package on Kali Linux

Last updated: December 24,2024

1. Install "python3-thinc" package

Please follow the steps below to install python3-thinc on Kali Linux

$ sudo apt update $ sudo apt install python3-thinc

2. Uninstall "python3-thinc" package

Please follow the steps below to uninstall python3-thinc on Kali Linux:

$ sudo apt remove python3-thinc $ sudo apt autoclean && sudo apt autoremove

3. Information about the python3-thinc package on Kali Linux

Package: python3-thinc
Source: python-thinc
Version: 8.2.2-1
Installed-Size: 4703
Maintainer: Debian Science Maintainers
Architecture: amd64
Depends: black, python3 (<< 3.13), python3 (>= 3.11~), python3-catalogue, python3-confection, python3-coverage, python3-cymem, python3-cython-blis, python3-flake8, python3-hypothesis, python3-importlib-resources | python3-supported-min (>= 3.7), python3-ipykernel, python3-isort, python3-mock, python3-murmurhash, python3-mypy | python3-supported-max (<< 3.7), python3-nbconvert, python3-nbformat, python3-numpy | python3-supported-max (<< 3.9), python3-numpy | python3-supported-min (>= 3.9), python3-packaging, python3-pkg-resources, python3-preshed, python3-pydantic, python3-pytest, python3-pytest-cov, python3-srsly, python3-typeshed, python3-typing-extensions | python3-supported-min (>= 3.8), python3-wasabi, python3:any, libc6 (>= 2.32), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2)
Size: 895648
SHA256: b3d0fb3f5ea56be6ae8f2f0e55f8796726ebdb7d6f809741e615975c77f1d7ae
SHA1: 9b30e24c0038e4ef995c234d0ade6fb780510134
MD5sum: 105557008eac96c74b2c06c1f94af838
Description: Practical Machine Learning for NLP in Python
Thinc is the machine learning library powering spaCy .
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 .
.
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.
Description-md5:
Homepage: https://thinc.ai/
Section: python
Priority: optional
Filename: pool/main/p/python-thinc/python3-thinc_8.2.2-1_amd64.deb