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bleuscore-js

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# bleuscore [![Crates.io](https://img.shields.io/crates/v/bleuscore)](https://crates.io/crates/bleuscore) [![PyPI - Version](https://img.shields.io/pypi/v/bleuscore)](https://pypi.org/project/bleuscore/) [![npm version](https://img.shields.io/npm/v/bleuscore-js)](https://www.npmjs.com/package/bleuscore-js) [![docs.rs](https://img.shields.io/docsrs/bleuscore)](https://docs.rs/bleuscore/0.1.3/bleuscore/) [![codecov](https://codecov.io/gh/shenxiangzhuang/bleuscore/graph/badge.svg?token=ckgU5oGbxf)](https://codecov.io/gh/shenxiangzhuang/bleuscore) [![MIT licensed](https://img.shields.io/badge/license-MIT-blue.svg)](./LICENSE) [![CodSpeed Badge](https://img.shields.io/endpoint?url=https://codspeed.io/badge.json)](https://codspeed.io/shenxiangzhuang/bleuscore) [`bleuscore`](https://github.com/shenxiangzhuang/bleuscore) is a fast BLEU score calculator written in rust. You can check try the web demo [here](https://shenxiangzhuang.github.io/bleuscore/) for a quick experience. ## Installation The python package has been published to [pypi](https://pypi.org/project/bleuscore/), so we can install it directly: - `uv`: `uv add bleuscore` - `pip`: `pip install bleuscore` ## Quick Start The usage is exactly same with [huggingface evaluate](https://huggingface.co/spaces/evaluate-metric/bleu): ```diff - import evaluate + import bleuscore predictions = ["hello there general kenobi", "foo bar foobar"] references = [ ["hello there general kenobi", "hello there !"], ["foo bar foobar"] ] - bleu = evaluate.load("bleu") - results = bleu.compute(predictions=predictions, references=references) + results = bleuscore.compute(predictions=predictions, references=references) print(results) # {'bleu': 1.0, 'precisions': [1.0, 1.0, 1.0, 1.0], 'brevity_penalty': 1.0, # 'length_ratio': 1.1666666666666667, 'translation_length': 7, 'reference_length': 6} ``` ## Benchmark **TLDR: We got more than 10x speedup when the corpus size beyond 100K** <p align="center"> <img src="./benchmark/bench.png" alt="Benchmark" width="400" height="300"> </p> We use the demo data shown in quick start to do this simple benchmark. You can check the [benchmark/simple](./benchmark/simple) for the benchmark source code. Detailed per-PR results are tracked automatically via the [Benchmark workflow](.github/workflows/benchmark.yml).