README.md

metadata

configs:
  - config_name: default
    data_files:
      - split: test
        path: indic_deva_eval.viewer.ocr.parquet
task_categories:
  - image-to-text
language:
  - ne
  - hi
  - mr
tags:
  - ocr
  - devanagari
  - glm-ocr
pretty_name: Indic Deva Eval

indic_deva_eval

Broad Indic Devanagari OCR benchmark across printed pages, digits, word crops, and handwriting.

• Repo: himalaya-ai/indic-deva-ocr-eval
• Task: indic_devanagari_ocr
• Main raw file: *.ocr.jsonl with image, ocr, source_repo, and language/provenance columns.
• Optional fine-tuning/eval file: *.sharegpt.json with messages and images.

Core Columns

• id: unique sample identifier
• image: relative path to the image file
• ocr: ground-truth text label

Source Mix

• devanagari_page_ocr default/test: 25%
• indic_vision_bench_deva_ocr ocr/test: 25%
• indic_mozhi_deva_word_ocr hindi/test: 15%
• indic_mozhi_deva_word_ocr marathi/test: 15%
• hindi_handwritten_word_ocr default/test: 15%
• devanagari_digits_mixed default/train: 5%

Notes

Generated by scripts/sample_ocr_eval_sets.py from the GLM fine-tuning workspace. If a source only exposes a train split, keep the deterministic held-out row ids out of SFT/training runs.