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bleu: Calculate BLEU Scores for Natural Language Generation Models

bleu simplifies the calculation of BLEU scores for natural language generation models by offering support for multiple languages and formats, making it a versatile choice for text evaluation.

Introduction:
bleu is a library designed for computing BLEU scores for natural language generation models. It's an exceptionally straightforward and user-friendly library that allows for quick and easy calculation of BLEU scores.

Overview:
bleu offers the following key features:

  1. Multi-language Support: bleu supports multiple languages, enabling users to choose their preferred language for BLEU score calculation.
  2. Multi-format Support: It also supports various formats, allowing users to select the format that best suits their needs.

bleu is a practical library for calculating BLEU scores for natural language generation models, known for its multi-language and multi-format support.

Recommendation:
For those in need of calculating BLEU scores for natural language generation models, bleu is highly recommended.

Usage Instructions:
To use bleu, follow these steps:

  1. Install bleu:
  2. Import bleu into your Python script:

Example Code:
Here's an example of how to use bleu to calculate BLEU scores in both English and Chinese:

# Calculate BLEU score in English
references = ["This is a sentence.", "This is another sentence."]
hypotheses = ["This is a sentence.", "This is another sentence."]
bleu_score = bleu.compute_bleu(references, hypotheses)

# Calculate BLEU score in Chinese
references = ["这是句子。", "这是另一句子。"]
hypotheses = ["这是句子。", "这是另一句子。"]
bleu_score = bleu.compute_bleu(references, hypotheses, language="zh")

Conclusion:
In conclusion, bleu is a practical library for calculating BLEU scores for natural language generation models, known for its multi-language and multi-format support.

About the author
Robert Harris

Robert Harris

I am a zealous AI info-collector and reporter, shining light on the latest AI advancements. Through various channels, I encapsulate and share innovation with a broader audience.

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