How to Enhance RAG Pipelines with Reasoning Using NVIDIA Llama Nemotron Models

A key challenge for retrieval-augmented generation (RAG) systems is handling user queries that lack explicit clarity or carry implicit intent. Users often…

A key challenge for retrieval-augmented generation (RAG) systems is handling user queries that lack explicit clarity or carry implicit intent. Users often phrase questions imprecisely. For instance, consider the user query, “Tell me about the latest update in NVIDIA NeMo model training.” It’s possible that the user is implicitly interested in advancements in NeMo large language model (LLM)…

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Source:: NVIDIA