Hello everyone, I am Weixue AI. Today I will introduce you to deep learning practice 50-Building ChatOCR project: OCR recognition question answering system based on large language model. This project is an OCR recognition question answering system based on deep learning and large language model. practical projects. This project aims to use deep learning technology and advanced large language models to build a system that can recognize text in images and answer questions related to the text.
In this project, we first need to collect training data, including labeled images and corresponding questions and answers. Use paddleOCR to build an OCR model for extracting text information from images. Then a ChatGLM large language model is introduced to generate answers based on the input questions. Large language models can have the ability to understand text semantics and generate coherent answers. We can provide the results of the question and OCR recognition to the large language model to generate corresponding answers.
In order to improve the performance of the system, some techniques are used in the detail part to improve the coherence and accuracy of the question answering process.
For the deployment of the ChatGLM large language model, please see:
Teach you how to deploy the Tsinghua large model ChatGLM-6B in the local CPU environment. Using the quantitative model, you can start smart chat locally, reaching 80% of ChatGPT