Arabic handwritten VLM

A user is seeking recommendations for the most accurate vision-language model (VLM) for extracting text from handwritten Arabic forms such as applications, questionnaires, and administrative documents. The request asks for benchmark results, model recommendations, and fine-tuning advice on models including Qwen-VL, Florence, PaliGemma, and Arabic-specific OCR/VLM systems, with a preference for offline or self-hosted inference. The user specifically wants high accuracy in Arabic handwritten text recognition, structured form understanding of fields, tables, and checkboxes, and mixed printed and handwritten Arabic content.

Hi everyone, Based on your experience, which trained VLM performs best for extracting text from handwritten Arabic forms e.g., applications, questionnaires, administrative documents ? I’m mainly looking for the highest possible accuracy in: - Arabic handwritten text recognition - Structured form understanding fields, tables, checkboxes - Mixed printed and handwritten Arabic content - Ideally offline/self-hosted inference Have you tested any models such as Qwen-VL, Florence, PaliGemma, or Arabic-specific OCR/VLM models on this type of document? If possible, I’d appreciate benchmark results, model recommendations, and fine-tuning advice. Thank you