Xiao, S., Liu, Z., Zhang, P., & Muennighoff, N. C-Pack: Packaged Resources To Advance General Chinese Embedding.
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Abstract
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The English models achieve state-of-the-art performance on the MTEB benchmark; meanwhile, the released English data and models for English text embeddings is 2 times larger than the Chinese data. We introduce C-Pack , a package of resources that significantly advance the field of general Chinese embeddings. C-Pack includes three critical resources. 1) C-MTEB is a comprehensive benchmark for Chinese text embeddings covering 6 tasks and 35 datasets. 2) C-MTP is a massive text embedding dataset curated from labeled and unlabeled Chinese corpora for training embedding models. 3) C-TEM is a family of embedding models covering multiple sizes. Our models outperform all prior Chinese text embeddings on C-MTEB by up to +10\% upon the time of the release. We also integrate and optimize the entire suite of training methods for C-TEM . Along with our resources on general Chinese embedding, we release our data and models for English text embeddings. The English models achieve state-of-the-art performance on the MTEB benchmark; meanwhile, our released English data is 2 times larger than the Chinese data. All these resources are made publicly available at https://github.com/FlagOpen/FlagEmbedding .
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