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# LayoutLM-Byne
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## The new SOTA in page retrieval from visually-rich documents.
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[![Logo](https://armalytix.s3.eu-west-2.amazonaws.com/TRUST+THE+COUNSEL+(1).png "Logo")](https://bynedocs.com "Logo")
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We're glad to introduce one of the first document page embedding models, LayoutLM-Byne.
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With the rise of multimodal LLMs, there is a growing adoption of applying models directly to a document without pre-processing it first, as was done before with RAG. This approach is significantly more robust than text-only RAG on a large subset of documents, especially visually rich ones.
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library_name: transformers
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# LayoutLM-Byne-v0.1
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## The new SOTA in page retrieval from visually-rich documents.
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[![Logo](https://armalytix.s3.eu-west-2.amazonaws.com/TRUST+THE+COUNSEL+(1).png "Logo")](https://bynedocs.com "Logo")
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We're glad to introduce one of the first document page embedding models, LayoutLM-Byne-v0.1.
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With the rise of multimodal LLMs, there is a growing adoption of applying models directly to a document without pre-processing it first, as was done before with RAG. This approach is significantly more robust than text-only RAG on a large subset of documents, especially visually rich ones.
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