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    Models/Zero Shot Classification/logic65/Whittle-Reflex-25B-A3B
    Zero Shot Classificationtransformersapache-2.0

    Whittle-Reflex-25B-A3B

    by logic65

    Identifier
    Model ID
    logic65/Whittle-Reflex-25B-A3B

    Deploy Whittle-Reflex-25B-A3B

    Single-tenant

    Mixpeek has no managed extractor for this model. On a single-tenant deployment you upload the weights and a custom plugin serves them next to the rest of your pipeline.

    Tags

    transformerssafetensorsqwen4_exp_texttext-generationsystem-onedecision-modelwhittleqwen4_expmixture-of-expertsknowledge-distillationcalibratedllama.cpppreviewzero-shot-classificationendataset:fancyzhx/ag_newsdataset:dair-ai/emotiondataset:CogComp/trecdataset:stanfordnlp/sst2dataset:nyu-mll/multi_nlidataset:stanfordnlp/snlidataset:Yelp/yelp_review_fulldataset:google/boolqdataset:tau/commonsense_qadataset:mteb/amazon_massive_intentdataset:allenai/ai2_arcdataset:Rowan/hellaswagdataset:allenai/winograndedataset:allenai/openbookqadataset:allenai/qasc

    Use Whittle-Reflex-25B-A3B 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, Whittle-Reflex-25B-A3B 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.