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    Models/Zero Shot Classification/pitangent-ds/deberta-v3-nli-onnx-quantized
    Zero Shot Classificationtransformersapache-2.0

    deberta-v3-nli-onnx-quantized

    by pitangent-ds

    Identifier
    Model ID
    pitangent-ds/deberta-v3-nli-onnx-quantized

    Tags

    transformersonnxdeberta-v2text-classificationORTModelForSequenceClassificationzero-shot-classificationenlicense:apache-2.0endpoints_compatibleregion:us

    Use deberta-v3-nli-onnx-quantized 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, deberta-v3-nli-onnx-quantized runs as a managed extractor inside a processing pipeline. Point a bucket of zero shot classification 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.