LiLT RoBERTa (base sized model) 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. Model description 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. Intended uses & limitations The model is meant to be fine tuned on tasks like document image classification, document parsing and document QA. See the model hub to look for fine tuned versions on a task that interests you. How to use For code examples, we refer to the documentation. BibTeX entry and citation info
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