layoutlmv2-base-uncased_finetuned_docvqa_on_1200
by sahil-everlign
4dl/month
Identifier
Model ID
sahil-everlign/layoutlmv2-base-uncased_finetuned_docvqa_on_1200Tags
transformerstensorboardsafetensorslayoutlmv2document-question-answeringgenerated_from_trainerbase_model:microsoft/layoutlmv2-base-uncasedbase_model:finetune:microsoft/layoutlmv2-base-uncasedlicense:cc-by-nc-sa-4.0endpoints_compatibleregion:us
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Open StudioHow It Runs on Mixpeek
On Mixpeek, layoutlmv2-base-uncased_finetuned_docvqa_on_1200 runs as a managed extractor inside a processing pipeline. Point a bucket of document 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.
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Specification
Organizationsahil-everlign
TaskDocument Question Answering
Librarytransformers
Licensecc-by-nc-sa-4.0
Downloads/mo4
View on HuggingFace
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