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    Models/Zero Shot Classification/schift-io/schift-nli
    Zero Shot Classificationtransformers.jsapache-2.0

    schift-nli

    by schift-io

    Identifier
    Model ID
    schift-io/schift-nli

    Tags

    transformers.jsonnxdeberta-v2text-classificationzero-shot-classificationnlischiftendataset:nyu-mll/multi_nlidataset:stanfordnlp/snlibase_model:cross-encoder/nli-deberta-v3-xsmallbase_model:quantized:cross-encoder/nli-deberta-v3-xsmalllicense:apache-2.0region:us

    Use schift-nli on Mixpeek

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

    Open Studio

    How It Runs on Mixpeek

    On Mixpeek, schift-nli 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.