#python #dataset #deep_learning #im2latex #im2markup #image_processing #image2text #latex #latex_ocr #machine_learning #math_ocr #ocr #pytorch #transformer #vision_transformer #vit
https://github.com/lukas-blecher/LaTeX-OCR
https://github.com/lukas-blecher/LaTeX-OCR
GitHub
GitHub - lukas-blecher/LaTeX-OCR: pix2tex: Using a ViT to convert images of equations into LaTeX code.
pix2tex: Using a ViT to convert images of equations into LaTeX code. - lukas-blecher/LaTeX-OCR
#python #glm #image2text #ocr
GLM-OCR is a top 0.9B-parameter model for accurate OCR on complex documents like tables, code, formulas, seals, and receipts, scoring 94.62 on OmniDocBench V1.5. Install via `pip install glmocr`, use cloud API (no GPU needed) or self-host with vLLM/SGLang for fast, low-cost inference, and get JSON/Markdown outputs easily via CLI or Python. You benefit from quick, robust document parsing that saves time, cuts compute costs, and integrates simply into your apps for real-world tasks.
https://github.com/zai-org/GLM-OCR
GLM-OCR is a top 0.9B-parameter model for accurate OCR on complex documents like tables, code, formulas, seals, and receipts, scoring 94.62 on OmniDocBench V1.5. Install via `pip install glmocr`, use cloud API (no GPU needed) or self-host with vLLM/SGLang for fast, low-cost inference, and get JSON/Markdown outputs easily via CLI or Python. You benefit from quick, robust document parsing that saves time, cuts compute costs, and integrates simply into your apps for real-world tasks.
https://github.com/zai-org/GLM-OCR
GitHub
GitHub - zai-org/GLM-OCR: GLM-OCR: Accurate × Fast × Comprehensive
GLM-OCR: Accurate × Fast × Comprehensive. Contribute to zai-org/GLM-OCR development by creating an account on GitHub.