stephantulkens/msmarco-gte-modernbert-pooled

这是sentence-transformers/msmarco-corpus数据集，使用了Alibaba-NLP/gte-modernbert-base模型进行嵌入。每个例子直接嵌入文本（没有额外的指令提示）。嵌入具有768的维度。这些嵌入旨在用于大规模蒸馏、检索和相似性搜索等任务。由于原始文本可能超过模型的限制，建议在构建时截断到模型的最大token长度。

This is the sentence-transformers/msmarco-corpus dataset, embedded with Alibaba-NLP/gte-modernbert-base. For each example, we embed the text directly (no additional instruction prompt). Embeddings have dimensionality 768. These embeddings are intended for tasks like large-scale distillation, retrieval, and similarity search. Because the raw text may exceed the models limit, we recommend truncating to the models maximum token length at build time.