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How to Fine-tuning Llama Vision OCR
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LLaMA OCR stands for “Large Language Model Application Optical Character Recognition”. It’s an optical character recognition technology that leverages large language models to recognize and convert text from images or documents into digital formats.
Key Aplications
- Text Recognition: Identifies text from images or documents.
- Digital Conversion: Converts text from images or documents into editable digital formats.
- Document Indexing: Assists in indexing documents for easier search and retrieval.
- Improved Accuracy: Enhances text recognition accuracy using large language models.
How it Works
LLaMA OCR employs large language models trained on extensive datasets to learn language patterns and structures. This enables the technology to recognize text with higher accuracy, even in challenging scenarios.
How to Train
For this project, we will be using google colab as our coding and computing environment, Unsloth as the fine-tuning framework, and the Invoice Recipts dataset. Unsloth is fast, consumes less GPU memory, and requires fewer lines of code compared to traditional methods.