Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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Document OCR using GLM-OCR

This dataset contains OCR results from images in minhpvo/ocr-input using GLM-OCR, a compact 0.9B OCR model achieving SOTA performance.

Processing Details

Source Dataset: minhpvo/ocr-input
Model: zai-org/GLM-OCR
Task: text recognition
Number of Samples: 13
Processing Time: 2.2 min
Processing Date: 2026-02-07 15:51 UTC

Configuration

Image Column: image
Output Column: markdown
Dataset Split: train
Batch Size: 16
Max Model Length: 8,192 tokens
Max Output Tokens: 16,384
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.py \
    minhpvo/ocr-input \
    <output-dataset> \
    --image-column image \
    --batch-size 16 \
    --task ocr

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