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yhan86
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mis1972image-glmocr

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./mis1972image/Screenshot 2026-03-26 at 09.56.56.png
TABLE 1. - U.S. receipts, production, consumption, shipments and stocks of iron and steel scrap and pig iron, by type of manufacturer (Short tons) | | FINAL JANUARY 1972 FIGURES | | | Total for month of January 1972 | Total year through January 1972 | Preliminary total for month of February 1972 | | :--- | :--- | :---...
[{"model_id": "zai-org/GLM-OCR", "model_name": "GLM-OCR", "column_name": "markdown", "timestamp": "2026-04-02T00:57:12.032534", "task": "ocr", "temperature": 0.01, "top_p": 1e-05, "repetition_penalty": 1.1, "max_tokens": 8192}]
./mis1972image/Screenshot 2026-03-26 at 09.57.16.png
TABLE 2. - Manufacturers of steel ingots and castings 1/ - receipts, production, consumption and shipments of iron and steel scrap, by grades, January 1972 (Short tons) | Item | Receipts | Production | Consumption | Shipments | Ending stocks | | :--- | :--- | :--- | :--- | :--- | :--- | | SCRAP: | | Carbon steel- | | ...
[{"model_id": "zai-org/GLM-OCR", "model_name": "GLM-OCR", "column_name": "markdown", "timestamp": "2026-04-02T00:57:12.032534", "task": "ocr", "temperature": 0.01, "top_p": 1e-05, "repetition_penalty": 1.1, "max_tokens": 8192}]
./mis1972image/Screenshot 2026-03-26 at 09.57.24.png
TABLE 3. - Manufacturers of steel castings 1/ - receipts, production, consumption and shipments of iron and steel scrap, by grades, January 1972 (Short tons) | Item | Receipts | Production | Consumption | Shipments | Ending stocks | | :--- | :--- | :--- | :--- | :--- | :--- | | **SCRAP:** | Carbon steel- | | | | | | |...
[{"model_id": "zai-org/GLM-OCR", "model_name": "GLM-OCR", "column_name": "markdown", "timestamp": "2026-04-02T00:57:12.032534", "task": "ocr", "temperature": 0.01, "top_p": 1e-05, "repetition_penalty": 1.1, "max_tokens": 8192}]
./mis1972image/Screenshot 2026-03-26 at 09.57.41.png
TABLE 4. - Iron foundries and miscellaneous users - receipts, production consumption and shipments of iron and steel scrap, by grades, January 1972 (Short tons) | Item | Receipts | Production | Consumption | Shipments | Ending stocks | | :--- | :--- | :--- | :--- | :--- | :--- | | **SCRAP:** | Carbon steel- | | | | | ...
[{"model_id": "zai-org/GLM-OCR", "model_name": "GLM-OCR", "column_name": "markdown", "timestamp": "2026-04-02T00:57:12.032534", "task": "ocr", "temperature": 0.01, "top_p": 1e-05, "repetition_penalty": 1.1, "max_tokens": 8192}]
./mis1972image/Screenshot 2026-03-26 at 09.57.51.png
TABLE 5. - U.S. exports of iron and steel scrap, $^{1/}$ by countries | Country | February 1972 | Value | Year to date | Value | | :--- | :--- | :--- | :--- | :--- | | Short tons | $26,101 | | $114 | $42,941 | | Belgium------- | 72 | | 156,117 | 5,042,209 | | Canada------- | 72,888 | 2,195,860 | 63 | 28,461 | | Hong K...
[{"model_id": "zai-org/GLM-OCR", "model_name": "GLM-OCR", "column_name": "markdown", "timestamp": "2026-04-02T00:57:12.032534", "task": "ocr", "temperature": 0.01, "top_p": 1e-05, "repetition_penalty": 1.1, "max_tokens": 8192}]
./mis1972image/Screenshot 2026-03-26 at 09.58.02.png
TABLE 6. - U.S. exports of iron and steel scrap, by grades Grades of scrap February 1972 Year to date Short tons Value Short tons Value No. 1 heavy melting steel scrap-------------------- 132,985 $4,196,322 219,740 $6,964,030 No. 2 heavy melting steel scrap-------------------- 39,947 1,072,954 76,667 2,017,029 No. 1 b...
[{"model_id": "zai-org/GLM-OCR", "model_name": "GLM-OCR", "column_name": "markdown", "timestamp": "2026-04-02T00:57:12.032534", "task": "ocr", "temperature": 0.01, "top_p": 1e-05, "repetition_penalty": 1.1, "max_tokens": 8192}]

Document OCR using GLM-OCR

This dataset contains OCR results from images in yhan86/mis1972image 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: 16
  • Max Model Length: 8,192 tokens
  • Max Output Tokens: 8,192
  • Temperature: 0.01
  • Top P: 1e-05
  • GPU Memory Utilization: 80.0%

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 

uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/glm-ocr-v2.py \
    yhan86/mis1972image \
    <output-dataset> \
    --image-column image \
    --batch-size 16 \
    --task ocr

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