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    Models/Text Classification/holistic-ai/rejection_detection
    Text Classificationtransformersapache-2.0

    rejection_detection

    by holistic-ai

    Identifier
    Model ID
    holistic-ai/rejection_detection

    Tags

    transformersonnxsafetensorsrobertatext-classificationgenerated_from_trainerrejectionno_answerchatgptendataset:argilla/notus-uf-dpo-closest-rejectedbase_model:distilbert/distilroberta-basebase_model:quantized:distilbert/distilroberta-baselicense:apache-2.0co2_eq_emissionstext-embeddings-inferenceendpoints_compatibleregion:us

    Use rejection_detection 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, rejection_detection runs as a managed extractor inside a processing pipeline. Point a bucket of text 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.