Model overview
This is a sentence-transformers model finetuned from Snowflake/snowflake-arctic-embed-l-v2.0 on the clustered datasets. It maps sentences & paragraphs to a 1024-dimensional dense vector space and can be used for semantic textual similarity, semantic search. The **Snowflake/snowflake-arctic-embed-l-v2.0** model has been further trained with Korean data to enhance its performance in **Korean retrieval tasks**. It is a powerful model that achieves **state-of-the-art (SOTA) performance across multiple retrieval benchmarks**. - **Model Type:** Sentence Transformer - **Base model:** Snowflake/snowflake-arctic-embed-l-v2.0 - **Maximum Sequence Length:** 8192 tokens - **Output Dimensionality:** 1024 dimensions - **Similarity Function:** Cosine Similarity - **Training Datasets:** - AI Hub Dataset - 행정 문서 대상 기계 독해 - 기계 독해 - 뉴스 기사 기계독해 - 도서 자료 기계독해 - 숫자 연산 기계독해 - 금융 법률 문서 기계독해 - **Language:** Korean, English
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
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Source prices & cost analysis
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Estimate monthly base token costs
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Public benchmarks & run configuration
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Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。