image imagewidth (px) 2.55k 14k | filename stringlengths 7 7 | paddleocr_table stringlengths 0 24.6k | inference_info stringclasses 1
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... | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] | |
002.jpg | overall dimension
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overall dimens... | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] | |
003.jpg | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] | ||
004.jpg | A4
Sample House street Address city, ST Zip | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] | |
005.jpg | BILL
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City, ST Zip | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] | |
006.jpg | Glazing Area
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0... | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] | |
007.jpg | A7
Sample House Street Address City, St Zip
Date:
Month 20th
Date:
Month 21st
Date:
Month 22nd
Date:
Month 23rd
Date:
Month 24th
Date:
Month 25th
Date:
Month 26th
Date:
Month 27th
Date:
Month 28th
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Month 29th
Date:
Month 30th
Date:
Month 31th
Date:
Month 32th
Date:
Month 33th
Date:
Month 34th
Date:
Month 35th
Date... | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] | |
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... | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] | |
009.png | <fcel>Half-Planet Name<fcel>Half-Ecliptic Name<fcel>Half-Ecliptic Radius (AU)<fcel>Ecliptic Radius (AU)<fcel>Ecliptic Radius (AU)<fcel>Ecliptic Radius (AU)<fcel>Ecliptic Radius (AU)<fcel>Ecliptic Radius (AU)<fcel>Ecliptic Radius (AU)<fcel>Ecliptic Radius (AU)<fcel>Ecliptic Radius (AU)<fcel>Ecliptic Radius (AU)<fcel>Ecl... | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] | |
010.png | <fcel>Half Plan at Top<lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lcel><lce... | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] | |
011.png | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] | ||
012.png | <fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称<fcel>项目名称... | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] | |
013.png | First Floor Plan | [{"model_id": "PaddlePaddle/PaddleOCR-VL", "model_name": "PaddleOCR-VL", "model_size": "0.9B", "task_mode": "table", "column_name": "paddleocr_table", "timestamp": "2026-02-09T04:02:46.641537", "temperature": 0.0, "max_tokens": 4096, "smart_resize": true}] |
Document Processing using PaddleOCR-VL (TABLE mode)
This dataset contains TABLE results from images in minhpvo/ocr-input using PaddleOCR-VL, an ultra-compact 0.9B OCR model.
Processing Details
- Source Dataset: minhpvo/ocr-input
- Model: PaddlePaddle/PaddleOCR-VL
- Task Mode:
table- Table extraction to HTML format - Number of Samples: 13
- Processing Time: 2.0 min
- Processing Date: 2026-02-09 04:02 UTC
Configuration
- Image Column:
image - Output Column:
paddleocr_table - Dataset Split:
train - Batch Size: 16
- Smart Resize: Enabled
- Max Model Length: 8,192 tokens
- Max Output Tokens: 4,096
- Temperature: 0.0
- GPU Memory Utilization: 80.0%
Model Information
PaddleOCR-VL is a state-of-the-art, resource-efficient model tailored for document parsing:
- 🎯 Ultra-compact - Only 0.9B parameters (smallest OCR model)
- 📝 OCR mode - General text extraction
- 📊 Table mode - HTML table recognition
- 📐 Formula mode - LaTeX mathematical notation
- 📈 Chart mode - Structured chart analysis
- 🌍 Multilingual - Support for multiple languages
- ⚡ Fast - Quick initialization and inference
- 🔧 ERNIE-4.5 based - Different architecture from Qwen models
Task Modes
- OCR: Extract text content to markdown format
- Table Recognition: Extract tables to HTML format
- Formula Recognition: Extract mathematical formulas to LaTeX
- Chart Recognition: Analyze and describe charts/diagrams
Dataset Structure
The dataset contains all original columns plus:
paddleocr_table: The extracted content based on task modeinference_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 extracted content
for example in dataset:
print(example["paddleocr_table"])
break
# View all OCR models applied to this dataset
inference_info = json.loads(dataset[0]["inference_info"])
for info in inference_info:
print(f"Task: {info['task_mode']} - Model: {info['model_id']}")
Reproduction
This dataset was generated using the uv-scripts/ocr PaddleOCR-VL script:
uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/paddleocr-vl.py \
minhpvo/ocr-input \
<output-dataset> \
--task-mode table \
--image-column image \
--batch-size 16 \
--max-model-len 8192 \
--max-tokens 4096 \
--gpu-memory-utilization 0.8
Performance
- Model Size: 0.9B parameters (smallest among OCR models)
- Processing Speed: ~0.11 images/second
- Architecture: NaViT visual encoder + ERNIE-4.5-0.3B language model
Generated with 🤖 UV Scripts
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