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Projects sharing features with OpenCLaP
30 open-source projects similar to thunlp/openclap, ranked by shared indexed features. Tags may describe platforms or build tools rather than the same primary purpose. Check each project’s use case, license, and deployment requirements before treating it as a replacement.
- ymcui/chinese-bert-wwm
ymcui/Chinese-BERT-wwm
10,212View on GitHubChinese-BERT-wwm is a pre-trained transformer model and encoder designed for Chinese natural language processing. It converts Chinese text into dense vector representations to be used across various natural language processing applications. The model utilizes a whole word masking strategy during pre-training, masking entire words rather than individual characters. This approach is designed to improve the capture of semantic meaning and language structure within Chinese datasets. The project covers a range of downstream tasks including text classification, sequence labeling, and reading compr
Pythonbertbert-wwmbert-wwm-ext - wainshine/chinese-names-corpus
wainshine/Chinese-Names-Corpus
4,303View on GitHubThis project is a curated collection of Chinese names, surnames, and kinship terms designed for linguistic analysis and natural language processing. It functions as a multilingual name dataset and a training resource for named entity recognition, providing a unified repository of names across Chinese, Japanese, and English languages. The project includes a synthetic name generator that creates realistic person names by applying analyzed naming patterns and demographic data. It also provides a cleaned Chinese idiom lexicon gathered and deduplicated from multiple sources. The available data su
corpusdatasetdict - embedding/chinese-word-vectors
Embedding/Chinese-Word-Vectors
12,227View on GitHubThis project is a collection of pre-trained dense and sparse word vectors trained on diverse Chinese corpora. It serves as a library of linguistic representations and an NLP vector dataset designed to improve the accuracy of semantic and morphological analysis in text models. The collection provides corpus-specific representations and utilizes n-gram co-occurrence modeling to capture diverse linguistic patterns. It includes a hybrid of dense-sparse vectors to balance computational efficiency and semantic precision. The project covers semantic vector search and the development of Chinese natu
Pythonchinesechinese-word-segmentationembedding
