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lilt-infoxlm-base

SCUT-DLVCLab

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

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Language-Independent Layout Transformer - RoBERTa model by stitching a pre-trained RoBERTa (English) and a pre-trained Language-Independent Layout Transformer (LiLT) together. It was introduced in the paper LiLT: A Simple yet Effective Language-Independent Layout Transformer for Structured Document Understanding by Wang et al. and first released in this repository. Disclaimer: The team releasing LiLT did not write a model card for this model so this model card has been written by the Hugging Face team. The Language-Independent Layout Transformer (LiLT) allows to combine any pre-trained RoBERTa encoder from the hub (hence, in any language) with a lightweight Layout Transformer to have a LayoutLM-like model for any language.

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Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
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lilt-infoxlm-base

lilt-roberta-en-base

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