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NLG-Eval is a toolkit for evaluating the quality of natural language generation (NLG) outputs using multiple automated metrics such as BLEU, METEOR, and ROUGE.
Features
- Implements multiple NLG evaluation metrics
- Supports sentence-level and corpus-level evaluations
- Works with machine translation, summarization, and chatbot output
- Provides command-line and Python API access
- Allows custom metric integration
- Optimized for large-scale NLG benchmarking
Project Samples
Categories
Natural Language Processing (NLP)License
MIT LicenseFollow NLG-Eval
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