Instructions to use IrakliJani/ka-ocr-v1-line with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use IrakliJani/ka-ocr-v1-line with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir ka-ocr-v1-line IrakliJani/ka-ocr-v1-line
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
ka-ocr v1 line OCR
This repository contains a single-line OCR model for Georgian-first typed text.
It is designed for machine-rendered screenshot-style text, not general document or camera OCR.
What this model is for
Use this model when your input is already close to a single horizontal text line, for example:
- cropped app or web screenshots
- quiz-card text lines
- social/news screenshot text lines
- other clean typed UI text
It works best on typed, machine-rendered text.
What this model is not for
This model is not a full multiline OCR system.
It does not do:
- page layout analysis
- paragraph or block segmentation
- multiline reading by itself
- handwriting OCR
- photo OCR for natural camera images
- scene text detection in arbitrary photos
If you want to use it on multiline screenshots, documents, or photos, you should first:
- detect the text regions yourself
- break the input into individual lines
- crop / deskew / normalize those lines
- run the model on each line separately
- join the line outputs yourself
In other words: treat this as a line recognizer, not a complete OCR pipeline.
Expected input
Best results come from inputs that are:
- screenshots or screenshot-like crops
- single-line
- reasonably horizontal
- reasonably sharp
- typed text, not handwriting
- high enough contrast between text and background
Output character support
The model is Georgian-first, but it can also emit Latin letters, digits, and punctuation from the included vocabulary.
See:
config.jsonvocab.jsonspecs.json
Files
best.safetensorsโ model weightsconfig.jsonโ minimal runtime configvocab.jsonโ public vocabulary definitionspecs.jsonโ model specs and validation metrics
Training data
Training for this project used:
Darsala/english_georgian_corporaโ English-Georgian Parallel Corpus by Luka Darsalia- a private author-created dataset
Most of the training data behind this released model came from the private dataset. The private dataset is not included in this repository.
Model summary
- architecture: CRNN + CTC single-line OCR
- image height: 48
- max width: 2048
- hidden size: 128
- width downsample: 4
- parameters: 1,200,414
Main validation snapshot from specs.json:
- CER: 0.00350
- WER: 0.01751
Limitations
This model can fail when:
- the input contains multiple lines at once
- the input is a photo instead of a screenshot-like crop
- the text is handwritten
- text is heavily warped, skewed, blurred, or perspective-distorted
- non-text graphics/icons are mixed into the same crop
- line detection/cropping is poor
License
This model is released under CC BY-NC 4.0.
That means attribution is required, and commercial use is not allowed.
See LICENSE for the short form and the official link.
Citation
If you use this model, please cite this model release. If relevant, also cite the public dataset used in the project.
Model citation
@misc{janiashvili2026ka_ocr_v1_line,
title={ka-ocr v1 line OCR},
author={Irakli Janiashvili},
year={2026},
url={https://huggingface.co/IrakliJani/ka-ocr-v1-line},
note={Single-line Georgian-first screenshot OCR model}
}
Dataset citation
@dataset{darsalia2025georgian_corpus,
title={English-Georgian Parallel Corpus},
author={Luka Darsalia},
year={2025},
url={https://huggingface.co/datasets/Darsala/english_georgian_corpora},
note={Bachelor thesis project - Tbilisi University}
}
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