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KaLM-Reranker-V1-Nano

Text Ranking
sentence-transformers
Safetensors
Transformers
multilingual
t5gemma2
text2text-generation
reranker
encoder-decoder
FBNL
Retrieval
RAG
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@@ -45,7 +45,6 @@ Extensive experiments on BEIR, MIRACL, and LMEB show that the KaLM-Reranker-V1 s
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  # Model Details
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- # The KaLM series model specifications
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  | Models | Activated Params. | Non-Embedding Params. | Embedding Params. | #Layers | Sequence Length | Document Token Dim. | MEP Support | Instruction Aware |
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  | ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- |
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  | [KaLM-Reranker-V1-Nano](https://huggingface.co/KaLM-Embedding/KaLM-Reranker-V1-Nano) | 0.27B | 100M | 168M | 18 | 128K | 640 | 1x-32x | Yes |
 
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  # Model Details
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  | Models | Activated Params. | Non-Embedding Params. | Embedding Params. | #Layers | Sequence Length | Document Token Dim. | MEP Support | Instruction Aware |
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  | ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- | ---- |
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  | [KaLM-Reranker-V1-Nano](https://huggingface.co/KaLM-Embedding/KaLM-Reranker-V1-Nano) | 0.27B | 100M | 168M | 18 | 128K | 640 | 1x-32x | Yes |