Datasets:

himalaya-ai
/

nepali-deva-ocr-eval

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

nepali_deva_eval

Nepali Devanagari OCR held-out slice for direct Nepali extraction quality.

Repo: himalaya-ai/nepali-deva-ocr-eval
Task: nepali_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

nepali_ocr_printed default/train: 100%

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.