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    Models/Text Generation/nvidia/NVIDIA-Nemotron-Nano-9B-v2-Japanese
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    NVIDIA-Nemotron-Nano-9B-v2-Japanese

    by nvidia

    119Kdl/month
    138likes
    Identifier
    Model ID
    nvidia/NVIDIA-Nemotron-Nano-9B-v2-Japanese

    Tags

    transformerssafetensorsnemotron_htext-generationnvidiapytorchconversationalcustom_codeenjadataset:nvidia/Nemotron-Personas-Japandataset:nvidia/Nemotron-CC-v2.1dataset:nvidia/Nemotron-Pretraining-Specialized-v1dataset:nvidia/Nemotron-Agentic-v1dataset:nvidia/Nemotron-Instruction-Following-Chat-v1dataset:globis-university/aozorabunko-cleandataset:HuggingFaceFW/fineweb-2arxiv:2504.03624arxiv:2508.14444base_model:nvidia/NVIDIA-Nemotron-Nano-9B-v2base_model:finetune:nvidia/NVIDIA-Nemotron-Nano-9B-v2license:otherendpoints_compatibleregion:us

    Use NVIDIA-Nemotron-Nano-9B-v2-Japanese on Mixpeek

    Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.

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    How It Runs on Mixpeek

    On Mixpeek, NVIDIA-Nemotron-Nano-9B-v2-Japanese runs as a managed extractor inside a processing pipeline. Point a bucket of text generation data at it, and Mixpeek handles GPU provisioning, batching, retries, and writing the outputs into a vector store you can query.

    Extractor outputs land in the Mixpeek Vector Store (MVS), where you can combine them with retrieval, reranking, and filter stages to build end-to-end search and agent-perception pipelines, no model-serving infrastructure to maintain.