layoutlmv2 base uncased

Introduction

LayoutLMv2 is an enhanced version of LayoutLM, designed to integrate text, layout, and image data into a unified multimodal framework. This model outperforms previous benchmarks, setting new state-of-the-art results on several visually-rich document understanding tasks, including FUNSD, CORD, SROIE, Kleister-NDA, RVL-CDIP, and DocVQA. Detailed information about its capabilities and performance is available in the associated research paper.

Architecture

LayoutLMv2 employs a multimodal architecture that captures interactions between text, layout, and images, facilitating improved document AI performance. This architecture allows for sophisticated understanding and processing of documents by modeling the relationships between different document elements.

Training

The pre-training tasks in LayoutLMv2 are designed to enhance the model's capability to learn from diverse data types in documents. The model is trained on a large corpus of documents, leveraging both textual and visual information to improve its understanding and processing of complex document layouts and formats.

Guide: Running Locally

To utilize the LayoutLMv2 model locally, follow these steps:

1. Installation: Ensure that you have the Hugging Face Transformers library and PyTorch installed. Use the following commands:

   pip install transformers
   pip install torch
   

2. Loading the Model: Load the LayoutLMv2 model using the Transformers library.

   from transformers import LayoutLMv2ForSequenceClassification, LayoutLMv2Tokenizer
   model = LayoutLMv2ForSequenceClassification.from_pretrained("microsoft/layoutlmv2-base-uncased")
   tokenizer = LayoutLMv2Tokenizer.from_pretrained("microsoft/layoutlmv2-base-uncased")
   

3. Data Preparation: Prepare your document data, ensuring it is compatible with the model's input requirements.
4. Inference: Run the model on your data to obtain predictions.

For enhanced performance, consider utilizing cloud GPUs from providers such as AWS, Google Cloud, or Azure.

License

The LayoutLMv2 model is released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License (cc-by-nc-sa-4.0), which allows for sharing and adapting the model for non-commercial purposes, provided appropriate credit is given and any derivatives are licensed under identical terms.