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@@ -11993,7 +11993,7 @@ UltraRAG-Embedding结构上采取双向注意力和 Weighted Mean Pooling [1]。
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  UltraRAG-Embedding incorporates bidirectional attention and Weighted Mean Pooling [1] in its architecture. The model underwent multi-stage training using approximately 260 million training examples, including open-source, synthetic, and proprietary data.
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- We also invite you to explore the RAG toolkit series:
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  - Retrieval Model: [UltraRAG-Embedding](https://huggingface.co/openbmb/UltraRAG-Embedding)
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  - Re-ranking Model: [UltraRAG-Reranker](https://huggingface.co/openbmb/UltraRAG-Reranker)
 
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  UltraRAG-Embedding incorporates bidirectional attention and Weighted Mean Pooling [1] in its architecture. The model underwent multi-stage training using approximately 260 million training examples, including open-source, synthetic, and proprietary data.
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+ We also invite you to explore the UltraRAG series:
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  - Retrieval Model: [UltraRAG-Embedding](https://huggingface.co/openbmb/UltraRAG-Embedding)
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  - Re-ranking Model: [UltraRAG-Reranker](https://huggingface.co/openbmb/UltraRAG-Reranker)