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README.md
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> [!WARNING]
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> ⚠️ The model supports both single-turn and multi-turn conversations.
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RAG systems enable AI solutions to include new, up-to-date, and potentially proprietary information in LLM responses that was not present in the training data. When a user asks a question, the retrieval component locates and delivers related documents from a knowledge base, and then the RAG generator model answers the question based on facts from those contextual documents.
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> [!WARNING]
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> ⚠️ The model supports both single-turn and multi-turn conversations.
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<center>
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<div style="text-align: center;">
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<img
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src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/Thv4Lq6wPYKNEAAJq_DtP.png"
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style="width: 100%; max-width: 50%; height: auto; display: inline-block;"
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/>
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</div>
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</center>
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RAG systems enable AI solutions to include new, up-to-date, and potentially proprietary information in LLM responses that was not present in the training data. When a user asks a question, the retrieval component locates and delivers related documents from a knowledge base, and then the RAG generator model answers the question based on facts from those contextual documents.
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