Instructions to use dh-unibe/trocr-medieval-escriptmask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use dh-unibe/trocr-medieval-escriptmask with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="dh-unibe/trocr-medieval-escriptmask")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("dh-unibe/trocr-medieval-escriptmask")
model = AutoModelForMultimodalLM.from_pretrained("dh-unibe/trocr-medieval-escriptmask", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use dh-unibe/trocr-medieval-escriptmask with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dh-unibe/trocr-medieval-escriptmask"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "dh-unibe/trocr-medieval-escriptmask",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/dh-unibe/trocr-medieval-escriptmask

SGLang

How to use dh-unibe/trocr-medieval-escriptmask with SGLang:

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-medieval-escriptmask" \
    --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-medieval-escriptmask",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use 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-medieval-escriptmask" \
        --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-medieval-escriptmask",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use dh-unibe/trocr-medieval-escriptmask with Docker Model Runner:
```
docker model run hf.co/dh-unibe/trocr-medieval-escriptmask
```

thodel commited on Mar 25, 2025

Commit

e293053

verified ·

1 Parent(s): 4122205

add metadata to model

Browse files

Files changed (1) hide show

README.md +7 -0

README.md CHANGED Viewed

@@ -14,8 +14,15 @@ language:
 - nl
 ---
 # TrOCR Medieval Model with linemasks generated in eScriptorium (https://de.wikipedia.org/wiki/EScriptorium)
 Base model: **microsoft/trocr-base-handwritten**
 Epochs: 19.05 / 20
 Eval CER: 0.0329

 - nl
 ---
 # TrOCR Medieval Model with linemasks generated in eScriptorium (https://de.wikipedia.org/wiki/EScriptorium)
+Handwritten Text Recognition model for Medieval Scripts.
+Part of the developments at the [Digital Humanities@University of Bern](https://www.dh.unibe.ch/).
+Developed by Jonas Widmer and Tobias Hodel based on different ground truth (see below).
 Base model: **microsoft/trocr-base-handwritten**
 Epochs: 19.05 / 20
 Eval CER: 0.0329