Datasets:

davanstrien
/

nanonets-ocr2-fix-test

document_id stringclasses 10 values	page_number stringclasses 10 values	text stringclasses 9 values	alto_xml stringclasses 10 values	has_image bool 1 class	has_alto bool 2 classes	markdown stringclasses 1 value	inference_info stringclasses 1 value
74972250	74974873	REPORT ON THE CALCUTTA MEDICAL INSTITUTIONS FOR THE YEAR 1878. No. 413B G. FROM THE SURGEON-GENERAL FOR BENGAL, To THE SECRETARY TO THE GOVERNMENT OF BENGAL. JUDICIAL AND POLITICAL DEPARTMENTS. Dated Calcutta, the 3rd April 1879. SIR, I HAVE the honor to submit the report of the following medical institutions of Calcut...	<?xml version="1.0" encoding="UTF-8"?> <alto xmlns="http://www.loc.gov/standards/alto/v3/alto.xsd"><Description><MeasurementUnit>pixel</MeasurementUnit><sourceImageInformation><fileName>./data/pdfs/c_75481908/i_74972250/74974873.6.pdf</fileName></sourceImageInformation><OCRProcessing ID="IdOcr"><ocrProcessingStep><proc...	true	true	!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!...	[{"model_id": "nanonets/Nanonets-OCR2-3B", "model_name": "Nanonets-OCR2-3B", "column_name": "markdown", "timestamp": "2026-06-30T17:31:59.238860", "batch_size": 16, "max_tokens": 15000, "gpu_memory_utilization": 0.8, "max_model_len": 32768, "script": "nanonets-ocr2.py", "script_url": "https://huggingface.co/datasets/uv...
91022596	91024490	24 HONORE. One Vaccinator under the Civil Surgeon, Assistant Surgeon H. WAKEFIELD. YEARS. 1864 1865 Total Vaccinated. 547 222 Compared with the preceding year. Increase. .... .... Decrease. .... 325 Success- fully Vaccinated. 475 177 Per-centage of Success. 86.8 79.7 The number vaccinated during the past year, shows a ...	<?xml version="1.0" encoding="UTF-8"?> <alto xmlns="http://www.loc.gov/standards/alto/v3/alto.xsd"><Description><MeasurementUnit>pixel</MeasurementUnit><sourceImageInformation><fileName>./data/pdfs/c_75481908/i_91022596/91024490.6.pdf</fileName></sourceImageInformation><OCRProcessing ID="IdOcr"><ocrProcessingStep><proc...	true	true	!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!...	[{"model_id": "nanonets/Nanonets-OCR2-3B", "model_name": "Nanonets-OCR2-3B", "column_name": "markdown", "timestamp": "2026-06-30T17:31:59.238860", "batch_size": 16, "max_tokens": 15000, "gpu_memory_utilization": 0.8, "max_model_len": 32768, "script": "nanonets-ocr2.py", "script_url": "https://huggingface.co/datasets/uv...
74990311	74991224	"Climate of the\nstation.\nVentilation\nand drainage\nf o r t h e m e n ' s\nhuts.\nSAUGOR CIRCLE.\n(...TRUNCATED)	"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<alto xmlns=\"http://www.loc.gov/standards/alto/v3/alto(...TRUNCATED)	true	true	"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!(...TRUNCATED)	"[{\"model_id\": \"nanonets/Nanonets-OCR2-3B\", \"model_name\": \"Nanonets-OCR2-3B\", \"column_name\(...TRUNCATED)
91029431	91032113	"13\nin the Bombay Presidency during the year 1907-08—continued.\nVACCINATION.\nSuccessful.\nOne a(...TRUNCATED)	"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<alto xmlns=\"http://www.loc.gov/standards/alto/v3/alto(...TRUNCATED)	true	true	"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!(...TRUNCATED)	"[{\"model_id\": \"nanonets/Nanonets-OCR2-3B\", \"model_name\": \"Nanonets-OCR2-3B\", \"column_name\(...TRUNCATED)
75033546	75033705			true	false	"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!(...TRUNCATED)	"[{\"model_id\": \"nanonets/Nanonets-OCR2-3B\", \"model_name\": \"Nanonets-OCR2-3B\", \"column_name\(...TRUNCATED)
75194196	75478039		"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<alto xmlns=\"http://www.loc.gov/standards/alto/v3/alto(...TRUNCATED)	true	true	"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!(...TRUNCATED)	"[{\"model_id\": \"nanonets/Nanonets-OCR2-3B\", \"model_name\": \"Nanonets-OCR2-3B\", \"column_name\(...TRUNCATED)
75006569	75007688	"NORTHERN DIVISION OF THE ARMY.\n95\nThe sub-soil water-level in the lines is, at all seasons of the(...TRUNCATED)	"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<alto xmlns=\"http://www.loc.gov/standards/alto/v3/alto(...TRUNCATED)	true	true	"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!(...TRUNCATED)	"[{\"model_id\": \"nanonets/Nanonets-OCR2-3B\", \"model_name\": \"Nanonets-OCR2-3B\", \"column_name\(...TRUNCATED)
75809782	75903720	"TABLE IX.\nShowing main results of the working of Provincial Cattle Farms during the year 1926-27.\(...TRUNCATED)	"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<alto xmlns=\"http://www.loc.gov/standards/alto/v3/alto(...TRUNCATED)	true	true	"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!(...TRUNCATED)	"[{\"model_id\": \"nanonets/Nanonets-OCR2-3B\", \"model_name\": \"Nanonets-OCR2-3B\", \"column_name\(...TRUNCATED)
91534624	91534874	"(RESOLUTION.)\nJUDICIAL DEPARTMENT.\nMedical.\nFort William, the 7th January 1870.\nTHIS report was(...TRUNCATED)	"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<alto xmlns=\"http://www.loc.gov/standards/alto/v3/alto(...TRUNCATED)	true	true	"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!(...TRUNCATED)	"[{\"model_id\": \"nanonets/Nanonets-OCR2-3B\", \"model_name\": \"Nanonets-OCR2-3B\", \"column_name\(...TRUNCATED)
91022598	91028977	"24\nin primary vaccinations, and is spread more or less over several of\nthe native states of this (...TRUNCATED)	"<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<alto xmlns=\"http://www.loc.gov/standards/alto/v3/alto(...TRUNCATED)	true	true	"!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!(...TRUNCATED)	"[{\"model_id\": \"nanonets/Nanonets-OCR2-3B\", \"model_name\": \"Nanonets-OCR2-3B\", \"column_name\(...TRUNCATED)

Document OCR using Nanonets-OCR2-3B

This dataset contains markdown-formatted OCR results from images in NationalLibraryOfScotland/medical-history-of-british-india using Nanonets-OCR2-3B.

Processing Details

Source Dataset: NationalLibraryOfScotland/medical-history-of-british-india
Model: nanonets/Nanonets-OCR2-3B
Model Size: 3.75B parameters
Number of Samples: 10
Processing Time: 13.4 minutes
Processing Date: 2026-06-30 17:32 UTC

Configuration

Image Column: image
Output Column: markdown
Dataset Split: train
Batch Size: 16
Max Model Length: 32,768 tokens
Max Output Tokens: 15,000
GPU Memory Utilization: 80.0%

Model Information

Nanonets-OCR2-3B is a state-of-the-art document OCR model that excels at:

📐 LaTeX equations - Mathematical formulas preserved in LaTeX format
📊 Tables - Extracted and formatted as HTML
📝 Document structure - Headers, lists, and formatting maintained
🖼️ Images - Captions and descriptions included in <img> tags
☑️ Forms - Checkboxes rendered as ☐/☑
🔖 Watermarks - Wrapped in <watermark> tags
📄 Page numbers - Wrapped in <page_number> tags
🌍 Multilingual - Supports multiple languages

Dataset Structure

The dataset contains all original columns plus:

markdown: The extracted text in markdown format with preserved structure
inference_info: JSON list tracking all OCR models applied to this dataset

Usage

from datasets import load_dataset
import json

# Load the dataset
dataset = load_dataset("{{output_dataset_id}}", split="train")

# Access the markdown text
for example in dataset:
    print(example["markdown"])
    break

# View all OCR models applied to this dataset
inference_info = json.loads(dataset[0]["inference_info"])
for info in inference_info:
    print(f"Column: {{info['column_name']}} - Model: {{info['model_id']}}")

Reproduction

This dataset was generated using the uv-scripts/ocr Nanonets OCR2 script:

uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/nanonets-ocr2.py \
    NationalLibraryOfScotland/medical-history-of-british-india \
    <output-dataset> \
    --model nanonets/Nanonets-OCR2-3B \
    --image-column image \
    --batch-size 16 \
    --max-model-len 32768 \
    --max-tokens 15000 \
    --gpu-memory-utilization 0.8

Performance

Processing Speed: ~0.0 images/second
GPU Configuration: vLLM with 80% GPU memory utilization

Generated with 🤖 UV Scripts

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Total file size:

1.07 MB