NEWVectors or files. Pick a path.Start →
    Models/Summarization/sysresearch101/t5-large-finetuned-xsum-cnn
    Summarizationtransformersmit

    t5-large-finetuned-xsum-cnn

    by sysresearch101

    Identifier
    Model ID
    sysresearch101/t5-large-finetuned-xsum-cnn

    Tags

    transformerspytorcht5text2text-generationsummarizationt5-large-summarizationpipeline:summarizationendataset:abisee/cnn_dailymaildataset:EdinburghNLP/xsumbase_model:google-t5/t5-largebase_model:finetune:google-t5/t5-largelicense:mitmodel-indextext-generation-inferenceendpoints_compatibleregion:us

    Use t5-large-finetuned-xsum-cnn 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, t5-large-finetuned-xsum-cnn runs as a managed extractor inside a processing pipeline. Point a bucket of summarization 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.