Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
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Updated
Nov 9, 2024 - Python
Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
This repository contains demos I made with the Transformers library by HuggingFace.
A Repo For Document AI
The MERIT Dataset is a fully synthetic, labeled dataset created for training and benchmarking LLMs on Visually Rich Document Understanding tasks. It is also designed to help detect biases and improve interpretability in LLMs, where we are actively working. This repository is actively maintained, and new features are continuously being added.
LayoutLMv3 applied to a VQA problem with infographics.
Exploring LayoutLM for Smart OCR Capabilities
Prototypical Networks for Information Extraction in Visual Documents. Weights can be found at https://drive.google.com/file/d/1Zrp7QaZIf0H_FFRx_LhB0uZTqDUSis2H/view?usp=sharing.
Fine-tuning LayoutLMv3 on the SROIE dataset to build a receipt understanding model
Mini Projects that are developed using Python.
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