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    Models/Visual Question Answering/freesky/InternVL-Chat-V1-5_ft_by_DecoVQAplus_SelectiveLoss

    InternVL-Chat-V1-5_ft_by_DecoVQAplus_SelectiveLoss

    by freesky

    Identifier
    Model ID
    freesky/InternVL-Chat-V1-5_ft_by_DecoVQAplus_SelectiveLoss

    Deploy InternVL-Chat-V1-5_ft_by_DecoVQAplus_SelectiveLoss

    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

    safetensorsinternvl_chatvisual-question-answeringcustom_codeenarxiv:2409.19339base_model:OpenGVLab/InternVL-Chat-V1-5base_model:finetune:OpenGVLab/InternVL-Chat-V1-5license:mitregion:us

    Use InternVL-Chat-V1-5_ft_by_DecoVQAplus_SelectiveLoss 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, InternVL-Chat-V1-5_ft_by_DecoVQAplus_SelectiveLoss runs as a managed extractor inside a processing pipeline. Point a bucket of visual question answering 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.