---
dataset_info:
  features:
  - name: image
    dtype: image
  - name: text
    dtype: string
  splits:
  - name: train
    num_bytes: 8961757.0
    num_examples: 4
  download_size: 8964031
  dataset_size: 8961757.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Example Dataset for Surya OCR Finetuning

This dataset is an example that lays out the expected format for finetuning Surya OCR. 

## Data Requirements
    Image column: The input images (full pages, blocks, or single text lines — mix freely).
    Text column: The transcription corresponding to each image.
        For math content, ensure <math display="inline"></math> or <math display="block"></math> tags are wrapped around the latex

## Surya OCR supports:
    Various aspect ratios
    Different image types and qualities
    Full-page documents
    Cropped blocks of text
    Single-line snippets

The base surya model is trained on a wide range of samples from all these categories, and you can combine any of these types in your training dataset for more robust performance, as demonstrated in this example dataset.