Image-Text-to-Text
Transformers
PyTorch
Safetensors
German
vision-encoder-decoder
trocr
kurrent
ocr
htr
19th century
How to use from
SGLangUse Docker images
docker run --gpus all \
--shm-size 32g \
-p 30000:30000 \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--env "HF_TOKEN=<secret>" \
--ipc=host \
lmsysorg/sglang:latest \
python3 -m sglang.launch_server \
--model-path "dh-unibe/trocr-kurrent" \
--host 0.0.0.0 \
--port 30000# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "dh-unibe/trocr-kurrent",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'Quick Links
TrOCR Kurrent-Model 19th century
Handwritten Text Recognition model for 19th century German.
Part of the developments at the Digital Humanities@University of Bern. Developed by Jonas Widmer and Tobias Hodel in conjunction with researchers and institutions mentioned below.
Base model: microsoft/trocr-base-handwritten
Train Lines: 292'997
Eval Lines: 7'513
Test Lines: 15'817
Epochs: 19.66 / 20
Eval CER: 0.02827
Test CER: 0.02655
Finetuned on Kurrent-dataset, containing:
- Material from the State Archives of Zurich ("Regierungsratsprotokolle"), provided by the State Archives of Zurich
- Lecture notes of Humboldt Lectures, provided by the Berlin-Brandenburgian Academy of Sciences
- Diary of Eugen Huber, provided by the University of Zurich
- Handwriting and Copies by and of Gottfried Semper (provided by the respective research project at ETH Zürich and USI Mendrisio)
- Konzilsprotokolle, University of Greifswald (19th century)
- as well as many other smaller collections/examples
The model has not been extensively tested. Potential biases are still to be identified.
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Model tree for dh-unibe/trocr-kurrent
Base model
microsoft/trocr-base-handwritten
Install from pip and serve model
# Install SGLang from pip: pip install sglang# Start the SGLang server: python3 -m sglang.launch_server \ --model-path "dh-unibe/trocr-kurrent" \ --host 0.0.0.0 \ --port 30000# Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dh-unibe/trocr-kurrent", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'