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  We introduce Dragon-multiturn, a retriever specifically designed for the conversational QA scenario. It can handle conversational query which combine dialogue history with the current query. It is built on top of the [Dragon](https://huggingface.co/facebook/dragon-plus-query-encoder) retriever. The details of Dragon-multiturn can be found in [here](https://arxiv.org/abs/2401.10225). **Please note that this repository is for the query encoder of Dragon-multiturn, and we use a separate model for the context encoder, which can be found [here](https://huggingface.co/nvidia/dragon-multiturn-context-encoder).**
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  ## Other Resources
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- [Llama3-ChatQA-1.5-8B](https://huggingface.co/nvidia/Llama3-ChatQA-1.5-8B)   [Llama3-ChatQA-1.5-70B](https://huggingface.co/nvidia/Llama3-ChatQA-1.5-70B)   [Evaluation Data](https://huggingface.co/datasets/nvidia/ChatRAG-Bench)   [Training Data](https://huggingface.co/datasets/nvidia/ChatQA-Training-Data)   [Paper](https://arxiv.org/abs/2401.10225)
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  ## Benchmark Results
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  <style type="text/css">
 
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  We introduce Dragon-multiturn, a retriever specifically designed for the conversational QA scenario. It can handle conversational query which combine dialogue history with the current query. It is built on top of the [Dragon](https://huggingface.co/facebook/dragon-plus-query-encoder) retriever. The details of Dragon-multiturn can be found in [here](https://arxiv.org/abs/2401.10225). **Please note that this repository is for the query encoder of Dragon-multiturn, and we use a separate model for the context encoder, which can be found [here](https://huggingface.co/nvidia/dragon-multiturn-context-encoder).**
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  ## Other Resources
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+ [Llama3-ChatQA-1.5-8B](https://huggingface.co/nvidia/Llama3-ChatQA-1.5-8B) &ensp; [Llama3-ChatQA-1.5-70B](https://huggingface.co/nvidia/Llama3-ChatQA-1.5-70B) &ensp; [Evaluation Data](https://huggingface.co/datasets/nvidia/ChatRAG-Bench) &ensp; [Training Data](https://huggingface.co/datasets/nvidia/ChatQA-Training-Data) &ensp; [Website](https://chatqa-project.github.io/) &ensp; [Paper](https://arxiv.org/abs/2401.10225)
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  ## Benchmark Results
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  <style type="text/css">