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    Models/Text Classification/ivanlau/language-detection-fine-tuned-on-xlm-roberta-base
    Text Classificationtransformersmit

    language-detection-fine-tuned-on-xlm-roberta-base

    by ivanlau

    Identifier
    Model ID
    ivanlau/language-detection-fine-tuned-on-xlm-roberta-base

    Deploy language-detection-fine-tuned-on-xlm-roberta-base

    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

    transformerspytorchtensorboardxlm-robertatext-classificationgenerated_from_trainerdataset:common_languagelicense:mitmodel-indextext-embeddings-inferenceendpoints_compatibleregion:usdeploy:azure

    Use language-detection-fine-tuned-on-xlm-roberta-base 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, language-detection-fine-tuned-on-xlm-roberta-base 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.