CoolFace
Datasetpublic

davanstrien/bpl-card-catalog-glm-ocr

Document OCR using GLM-OCR This dataset contains OCR results from images in davanstrien/bpl-card-catalog-with-ocr using GLM-OCR, a compact 0.9B OCR model achieving SOTA performance. Processing Details Source Dataset: davanstrien/bpl-card-catalog-with-ocr Model: zai-org/GLM-OCR Task: text recognition Number of Samples: 453,006 Processing Time: 1315.3 min Processing Date: 2026-02-27 11:43 UTC Configuration Image Column: image Output Column:… See the full description on the dataset page: https://huggingface.co/datasets/davanstrien/bpl-card-catalog-glm-ocr.

sourceHugging Faceupdated 7mo agoView on Hugging Face
0likes94downloads
Dataset Card

Document OCR using GLM-OCR

This dataset contains OCR results from images in davanstrien/bpl-card-catalog-with-ocr using GLM-OCR, a compact 0.9B OCR model achieving SOTA performance.

Processing Details

Configuration

  • —Image Column: image
  • —Output Column: markdown
  • —Dataset Split: train
  • —Batch Size: 64
  • —Max Model Length: 8,192 tokens
  • —Max Output Tokens: 8,192
  • —Temperature: 0.01
  • —Top P: 1e-05
  • —GPU Memory Utilization: 90.0%

Model Information

GLM-OCR is a compact, high-performance OCR model:

  • —0.9B parameters
  • —94.62% on OmniDocBench V1.5
  • —CogViT visual encoder + GLM-0.5B language decoder
  • —Multi-Token Prediction (MTP) loss for efficiency
  • —Multilingual: zh, en, fr, es, ru, de, ja, ko
  • —MIT licensed

Dataset Structure

The dataset contains all original columns plus:

  • —markdown: The extracted text in markdown format
  • —inference_info: JSON list tracking all OCR models applied to this dataset

Reproduction

bash
uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/glm-ocr-v2.py \
    davanstrien/bpl-card-catalog-with-ocr \
    <output-dataset> \
    --image-column image \
    --batch-size 64 \
    --task ocr

Generated with UV Scripts (glm-ocr-v2.py)