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GitHub / worldbank / REaLTabFormer

A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/worldbank%2FREaLTabFormer

Stars: 187
Forks: 22
Open Issues: 26

License: mit
Language: Jupyter Notebook
Repo Size: 6.12 MB
Dependencies: 25

Created: over 1 year ago
Updated: 2 days ago
Last pushed: about 1 month ago
Last synced: about 7 hours ago

Commit Stats

Commits: 26
Authors: 3
Mean commits per author: 8.67
Development Distribution Score: 0.077
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/worldbank/REaLTabFormer

Topics: data-generation, deep-learning, gpt, gpt-2, seq2seq-model, synthetic-data, synthetic-dataset-generation, tabular-data, transformers

Files
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    Readme
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    Dependencies
    setup.py pypi