name2gender 0.0.5a0

From names in multiple languages to genders.

Name2Gender

From names in multiple languages to genders.

Installation

• From PyPi

pip install -U name2gender

or

uv add -U name2gender

• From Github

pip install git+https://github.com/vortezwohl/Name2Gender.git

Quick Start

1. Import SDKs

   from name2gender import Name2Gender, Gender
   

2. Gender recognition based on names

   n2g = Name2Gender()
   names = ['吴子豪', '吴彦祖', '梅艳芳', '张曼玉',
            'Donald Trump', 'Ivanka Trump',
            'Justin Bieber', 'The Weeknd',
            'Luigi Nicholas Mangione',
            'Elizabeth II', 'Henry VIII']
   for name in names:
       _gender, _prob = n2g(name, return_probability=True)
       print(name, 'is', _gender, 'with a probability of', f'{_prob * 100:.2f}%')
   

   stdout:

   吴子豪 is Gender.Male with a probability of 99.71%
   吴彦祖 is Gender.Male with a probability of 100.00%
   梅艳芳 is Gender.Female with a probability of 99.99%
   张曼玉 is Gender.Female with a probability of 99.92%
   Donald Trump is Gender.Male with a probability of 99.90%
   Ivanka Trump is Gender.Female with a probability of 99.66%
   Justin Bieber is Gender.Male with a probability of 100.00%
   The Weeknd is Gender.Male with a probability of 97.66%
   Luigi Nicholas Mangione is Gender.Male with a probability of 99.27%
   Elizabeth II is Gender.Female with a probability of 99.71%
   Henry VIII is Gender.Male with a probability of 99.90%
   

Use Name2Gender with CLI

1. Install model

   n2g install name2gender-small
   

   stdout:

   Successfully installed model "name2gender-small".
   

2. Predict genders

   n2g predict LadyGaga
   

   stdout:

   "LadyGaga" is FEMALE with an probability of 99.64%.
   

3. Uninstall model

   n2g uninstall name2gender-small
   

   stdout:

   Model "name2gender-small" is uninstalled.