Maluuba/nlg-eval

Evaluation code for various unsupervised automated metrics for Natural Language Generation.

49
/ 100
Emerging

Implements nine metrics spanning n-gram overlap (BLEU, METEOR, ROUGE, CIDEr, SPICE) and semantic similarity approaches (SkipThought, GloVe embeddings, greedy matching). The toolkit provides both CLI and Python APIs (functional and object-oriented) for corpus-level and sentence-level evaluation, with pre-trained models and embeddings downloaded automatically during setup.

1,391 stars. No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 23 / 25

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Python

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Last pushed

Aug 20, 2024

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