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CoIR (Code Information Retrieval Benchmark) is the first comprehensive benchmark designed to evaluate models' abilities in code retrieval. It includes four distinct tasks: text-to-code retrieval, code-to-text retrieval, code-to-code retrieval, and hybrid-code retrieval. The benchmark encompasses a total of 10 datasets, covering 14 programming languages and containing 2 million evaluation documents.
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CoIR (Code Information Retrieval Benchmark) is the **first** comprehensive benchmark designed to evaluate models' abilities in code retrieval. It includes four distinct code retrieval tasks: text-to-code retrieval, code-to-text retrieval, code-to-code retrieval, and hybrid-code retrieval. The benchmark encompasses a total of 10 datasets, covering 14 programming languages and containing 2 million evaluation documents. For comprehensive details, please refer to our [GitHub repository](https://github.com/CoIR-team/coir) and the associated [research paper](https://arxiv.org/abs/2407.02883)
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