yuan2005 · PyLaia · Published February 2, 2026
John Locke HTR Model
Text Recognition
Description
This Handwritten Text Recognition (HTR) model is specifically optimized for transcribing the manuscripts of the philosopher John Locke (1632–1704). It was trained using the "B2022 English Model M4" as a base model to ensure high stability. It is highly suitable for researchers working on Locke's correspondence and philosophical drafts.
Try this model
Drag an image here
Select a file...PNG or JPG up to 10 Mb
Wolpi
AI Assistant
By uploading an image, you accept our terms and privacy policy.
Use this modelOpen in Transkribus
Low error rate6.11% CER
Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 6.11% on its validation set. As a rule of thumb, a CER below 10% is considered good for most handwritten material.
Measured on the model's own validation data. Results on your documents may differ depending on handwriting style, document condition, language, and how closely your material resembles the training data.
Words14,548
Lines2,092
Training Pages98
Model ID502557