Turmbücher LM
This repository contains the language models (forward & backward) that were used to train the Turmbücher NER.
Two models for premodern German trained by Ismail Prada Ziegler as part of a research project at the University of Bern, Digital Humanities.
We recommend using flairs stacked embeddings for best effect.
Data Set
Main data set: Berner Turmbücher, early volumes from 16th C., Early New High German, 61k tokens training data.
Secondary data sets:
- SSRQ - Fribourg, 59k tokens.
- Chorgerichtsmanuale (unpublished), 76k tokens.
- Königsfelden Charters, 623k tokens.
- Talgerichtsprotokolle (unpublished), 438k tokens.
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Inference Providers
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This model is not currently available via any of the supported third-party Inference Providers, and
the HF Inference API does not support flair models with pipeline type text-generation