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embeddings-pre-training|自然语言处理数据集|机器学习数据集
收藏魔搭社区2025-08-22 更新2025-08-23 收录
下载链接：
https://modelscope.cn/datasets/lightonai/embeddings-pre-training
下载链接
链接失效反馈资源简介：
This large-scale dataset aggregates diverse, contrastive pre-training data curated for developing state-of-the-art text embedding models.
The collection is primarily in English, with the inclusion of several French datasets to facilitate bilingual and cross-lingual research.
| Dataset | MGTE Training | Language | Source |
| :---------------------------------- | :-----------: | :------------ | :----- |
| agnews | ✅ | English | [st](https://huggingface.co/datasets/sentence-transformers/agnews) |
| altlex | | English | [st](https://huggingface.co/datasets/sentence-transformers/altlex) |
| amazon_qa | ✅ | English | [nomic](https://huggingface.co/datasets/nomic-ai/nomic-embed-unsupervised-data) |
| amazon_reviews | | English | [st](https://huggingface.co/datasets/sentence-transformers/amazon-reviews) |
| arxiv_title_abstract | ✅ | English | [universetdb](https://huggingface.co/datasets/UniverseTBD/arxiv-abstracts-large) |
| beir_dbpedia | ✅ | English | [beir](https://huggingface.co/datasets/BeIR/dbpedia-entity) |
| biorxiv_title_abstract | ✅ | English | [laion](https://huggingface.co/datasets/laion/biorXiv_metadata) |
| cnn_dailymail | ✅ | English | [st](https://huggingface.co/datasets/sentence-transformers/embedding-training-data) |
| codesearchnet | | English | [st](https://huggingface.co/datasets/sentence-transformers/codesearchnet) |
| cc_news_fr | | French | [intfloat](https://huggingface.co/datasets/intfloat/multilingual_cc_news) |
| cc_news_en | | English | [nomic](https://huggingface.co/datasets/nomic-ai/nomic-embed-unsupervised-data) |
| eli5 | | English | [st](https://huggingface.co/datasets/sentence-transformers/eli5) |
| gooaq_qa | ✅ | English | [st](https://huggingface.co/datasets/sentence-transformers/embedding-training-data) |
| medrxiv_title_abstract | ✅ | English | [mteb](https://huggingface.co/datasets/mteb/raw_medrxiv) |
| nllb_eng_fra | | Cross lingual | [allenai](https://huggingface.co/datasets/allenai/nllb) |
| npr | ✅ | English | [st](https://huggingface.co/datasets/sentence-transformers/npr) |
| paq | | English | [st](https://huggingface.co/datasets/sentence-transformers/paq) |
| reddit | ✅ | English | [st](https://huggingface.co/datasets/sentence-transformers/reddit) |
| s2orc_abstract_citation | | English | [st](https://huggingface.co/datasets/sentence-transformers/s2orc) |
| s2orc_citation_titles | ✅ | English | [st](https://huggingface.co/datasets/sentence-transformers/s2orc) |
| s2orc_title_abstract | ✅ | English | [st](https://huggingface.co/datasets/sentence-transformers/s2orc) |
| sentence_compression | | English | [st](https://huggingface.co/datasets/sentence-transformers/sentence-compression) |
| simplewiki | | English | [st](https://huggingface.co/datasets/sentence-transformers/simple-wiki) |
| stackexchange_body_body | | English | [st](https://huggingface.co/datasets/sentence-transformers/stackexchange-duplicates) |
| stackexchange_duplicate_questions | | English | [st](https://huggingface.co/datasets/sentence-transformers/stackexchange-duplicates) |
| stackexchange_qa | ✅ | English | [flax](https://huggingface.co/datasets/flax-sentence-embeddings/stackexchange_title_best_voted_answer_jsonl) |
| stackexchange_title_body | ✅ | English | [flax](https://huggingface.co/datasets/flax-sentence-embeddings/stackexchange_title_best_voted_answer_jsonl) |
| stackoverflow_title_body | ✅ | English | [flax](https://huggingface.co/datasets/flax-sentence-embeddings/stackexchange_title_best_voted_answer_jsonl) |
| webfaq_eng | | English | [padas-lab](https://huggingface.co/datasets/PaDaS-Lab/webfaq) |
| webfaq_fra | | French | [padas-lab](https://huggingface.co/datasets/PaDaS-Lab/webfaq) |
| wikihow | ✅ | English | [st](https://huggingface.co/datasets/sentence-transformers/embedding-training-data) |
| yahoo_answer | | English | [st](https://huggingface.co/datasets/sentence-transformers/embedding-training-data) |
| yahoo_qa | ✅ | English | [st](https://huggingface.co/datasets/sentence-transformers/yahoo-answers/viewer/title-answer-pair) |
| yahoo_question_body | ✅ | English | [st](https://huggingface.co/datasets/sentence-transformers/embedding-training-data) |
提供机构：
maas
创建时间：
2025-08-19
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