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    Models/Zero Shot Classification/sknow-lab/Qwen2.5-14B-CIC-ACLARC
    Zero Shot Classificationtransformersapache-2.0

    Qwen2.5-14B-CIC-ACLARC

    by sknow-lab

    Identifier
    Model ID
    sknow-lab/Qwen2.5-14B-CIC-ACLARC

    Tags

    transformerssafetensorsqwen2text-generationscientometricscitation_analysiscitation_intent_classificationzero-shot-classificationendataset:kejian/ACL-ARCarxiv:2502.14561base_model:Qwen/Qwen2.5-14B-Instructbase_model:finetune:Qwen/Qwen2.5-14B-Instructlicense:apache-2.0text-generation-inferenceendpoints_compatibleregion:us

    Use Qwen2.5-14B-CIC-ACLARC 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, Qwen2.5-14B-CIC-ACLARC 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.