Science Score: 57.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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✓DOI references
Found 3 DOI reference(s) in README -
○Academic publication links
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○Scientific vocabulary similarity
Low similarity (9.4%) to scientific vocabulary
Keywords
generative-modeling
names
pytorch
Last synced: 6 months ago
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JSON representation
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Repository
generative model for names
Basic Info
Statistics
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 0
- Releases: 0
Topics
generative-modeling
names
pytorch
Created over 3 years ago
· Last pushed 6 months ago
Metadata Files
Readme
License
Citation
README.rst
naamkaran: generative model for names
-------------------------------------
.. image:: https://github.com/appeler/naamkaran/actions/workflows/python-package.yml/badge.svg
:target: https://github.com/appeler/naamkaran/actions?query=workflow%3Apython-package
.. image:: https://img.shields.io/pypi/v/naamkaran.svg
:target: https://pypi.python.org/pypi/naamkaran
.. image:: https://static.pepy.tech/badge/naamkaran
:target: https://pepy.tech/project/naamkaran
Naamkaran is a generative model for names. It is based on a character-level RNN trained on names from the Florida Voter Registration Data.
Gradio App.
------------
`Naamkaran on HF `__
Installation
------------
Naamkaran can be installed from PyPI using pip:
.. code-block:: bash
pip install naamkaran
For development with all tools:
.. code-block:: bash
pip install -e ".[dev,test]"
For web applications (Gradio/Flask):
.. code-block:: bash
pip install "naamkaran[web]"
General API
-----------
The general API for naamkaran is as follows:
::
# naamkaran is the package name
from naamkaran.generate import generate_names
# generate_names is the function that generates names
positional arguments:
start_letter The letter to start the name with (default: "a")
optional arguments:
end_letter The letter to end the name with (default: None)
how_many The number of names to generate (default: 1)
max_length The maximum length of the name (default: 5)
gender The gender of the name (default: "M")
temperature The temperature of the model (default: 0.5)
# generate 10 names starting with 'A'
generate_names('A', how_many=10)
['Allis', 'Alber', 'Aderi', 'Albri', 'Alawa',
'Arver', 'Agnee', 'Anous', 'Areyd', 'Adria']
# generate 10 names starting with 'B' and ending with 'n'
generate_names('B', end_letter='n', how_many=10)
['Brian', 'Beran', 'Burin', 'Bahan', 'Balin',
'Bounn', 'Baran', 'Balan', 'Belin', 'Brion']
# generate 5 names starting with 'B' and ending with 'n' with a maximum length of 4
generate_names('B', end_letter='n', how_many=5, max_length=4)
['Bern', 'Bren', 'Bran', 'Bonn', 'Brun']
# generate 10 names starting with 'D' and ending with 'd' with a maximum length of 6
# and a temperature of 0.5
generate_names('D', end_letter='d', how_many=5, max_length=6, temperature=0.5)
['Derayd', 'Davind', 'Deland', 'Denild', 'David']
# generate 10 female names starting with 'A' and ending with 'e' with a maximum length of 5
# and a temperature of 0.5
generate_names('A', end_letter='e', how_many=10, max_length=5, gender="F", temperature=0.5)
['Annhe', 'Annie', 'Altre', 'Anne', 'Ashle',
'Arine', 'Anice', 'Andre', 'Anale', 'Allie']
Data
----
The model is trained on names from the Florida Voter Registration Data from early 2022.
The data are available on the `Harvard Dataverse `__
Authors
-------
Rajashekar Chintalapati and Gaurav Sood
Contributing
------------
Contributions are welcome. Please open an issue if you find a bug or have a feature request.
License
-------
The package is released under the `MIT License `_.
Owner
- Name: appeler
- Login: appeler
- Kind: organization
- Website: https://appeler.github.io/
- Repositories: 24
- Profile: https://github.com/appeler
Making sense of names.
Citation (Citation.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Chintalapati" given-names: "Rajashekar" - family-names: "Sood" given-names: "Gaurav" title: "naamkaran: name generator" version: 0.1.0 date-released: 2023-08-29 url: "https://github.com/appeler/naamkaran"
GitHub Events
Total
- Delete event: 6
- Issue comment event: 1
- Push event: 12
- Pull request event: 10
- Create event: 4
Last Year
- Delete event: 6
- Issue comment event: 1
- Push event: 12
- Pull request event: 10
- Create event: 4
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 0
- Total pull requests: 13
- Average time to close issues: N/A
- Average time to close pull requests: 2 months
- Total issue authors: 0
- Total pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.08
- Merged pull requests: 7
- Bot issues: 0
- Bot pull requests: 13
Past Year
- Issues: 0
- Pull requests: 9
- Average time to close issues: N/A
- Average time to close pull requests: 5 days
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 6
- Bot issues: 0
- Bot pull requests: 9
Top Authors
Issue Authors
Pull Request Authors
- dependabot[bot] (13)
Top Labels
Issue Labels
Pull Request Labels
dependencies (13)
python (9)
Packages
- Total packages: 1
-
Total downloads:
- pypi 109 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 3
- Total maintainers: 2
pypi.org: naamkaran
Generative model for names.
- Homepage: https://github.com/appeler/naamkaran
- Documentation: https://naamkaran.readthedocs.io/
- License: MIT
-
Latest release: 0.1.0
published 6 months ago
Rankings
Dependent packages count: 7.5%
Average: 38.7%
Dependent repos count: 69.8%
Maintainers (2)
Last synced:
6 months ago
Dependencies
requirements-rtd.txt
pypi
- joblib ==1.3.2
- pandas ==2.0.3
- pytest ==7.4.0
- scikit-learn ==1.3.0
- torch ==2.0.1
requirements.txt
pypi
- joblib ==1.3.2
- pandas ==2.0.3
- pytest ==7.4.0
- scikit-learn ==1.3.0
- torch ==2.0.1
setup.py
pypi
- joblib ==1.3.2
- torch ==2.0.1