AIArchiveInfo/Yuan-embedding-2.0-zh

Byte-identical preservation mirror of `IEITYuan/Yuan-embedding-2.0-zh` at revision `fb4ab1ed9d34`, archived 2026-09-25 by AIArchive. All credit belongs to the original authors. No weights were trained, fine-tuned, or altered in any way. The original license (apache-2.0) is included verbatim and continues to govern this copy.

<h2 align="left">Yuan-embedding-2.0-zh</h2>

Yuan-embedding-2.0-zh 是专门为中文文本检索任务设计的嵌入模型。我们在Yuan-embedding-1.0的基础上，针对Retrieval任务与Reranking任务进行了进一步优化。主要工作如下：

• —数据增强
• —Hard negative sampling：利用Rerank模型与LLM进行双重评估，筛选出高质量正负样本
• —LLM合成数据：利用Yuan2-M32针对训练数据query进行LLM重写
• —损失函数设计
• —Multi-Task loss
• —Matryoshka Representation Learning
• —Retrieval任务使用InfoNCE with in-batch-negative
• —针对Reranking任务设计Margin-Adaptive Pairwise Ranking Loss

<h2 align="left">Usage</h2>

pip install -U sentence-transformers==3.4.1

使用示例：

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("IEITYuan/Yuan-embedding-2.0-zh")
sentences_1 = ["样例数据-1", "样例数据-2"]
sentences_2 = ["样例数据-3", "样例数据-4"]
embeddings_1 = model.encode(sentences_1, normalize_embeddings=True)
embeddings_2 = model.encode(sentences_2, normalize_embeddings=True)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)