--- base_model: unsloth/qwen2-vl-7b-instruct-unsloth-bnb-4bit library_name: transformers model_name: outputs tags: - generated_from_trainer - urdu_ocr licence: license --- # Model Card for outputs This model is a fine-tuned version of [unsloth/qwen2-vl-7b-instruct-unsloth-bnb-4bit](https://huggingface.co/unsloth/qwen2-vl-7b-instruct-unsloth-bnb-4bit). It has been trained using [TRL](https://github.com/huggingface/trl). ##A transformer-based OCR model fine-tuned for recognizing Urdu text from images. This repository contains a fine-tuned VisionEncoderDecoderModel built on top of TrOCR for Urdu Optical Character Recognition (OCR). The model is trained to extract Urdu text from scanned documents, printed pages, and image-based text inputs. Open model View benchmark notebook ``` ## Highlights Fine-tuned specifically for Urdu script recognition. Works on scanned pages, screenshots, and cropped text regions. Built using Hugging Face Transformers and TrOCR. Easy inference pipeline with minimal code.. ### Quick Start Install dependencies Load the model Run inference ###Training Procedure This model was fine-tuned using supervised learning on paired image–text data for Urdu OCR. ###Training details ###Parameter Value Base model microsoft/trocr-base-handwritten Task Sequence-to-sequence OCR Framework Transformers Trainer API Optimization Cross-entropy loss ###Intended Use ###Suitable for Digitizing Urdu books and documents. Extracting text from scanned PDFs. OCR preprocessing for NLP pipelines. Research and educational projects involving Urdu script. ## Citations Cite TRL as: ```bibtex @misc{vonwerra2022trl, title = {{TRL: Transformer Reinforcement Learning}}, author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} } ```