|
--- |
|
language: de |
|
license: mit |
|
tags: |
|
- "historic german" |
|
--- |
|
|
|
# 🤗 + 📚 dbmdz ConvBERT model |
|
|
|
In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State |
|
Library open sources a German Europeana ConvBERT models 🎉 |
|
|
|
# German Europeana ConvBERT |
|
|
|
We use the open source [Europeana newspapers](http://www.europeana-newspapers.eu/) |
|
that were provided by *The European Library*. The final |
|
training corpus has a size of 51GB and consists of 8,035,986,369 tokens. |
|
|
|
Detailed information about the data and pretraining steps can be found in |
|
[this repository](https://github.com/stefan-it/europeana-bert). |
|
|
|
## Results |
|
|
|
For results on Historic NER, please refer to [this repository](https://github.com/stefan-it/europeana-bert). |
|
|
|
## Usage |
|
|
|
With Transformers >= 4.3 our German Europeana ConvBERT model can be loaded like: |
|
|
|
```python |
|
from transformers import AutoModel, AutoTokenizer |
|
|
|
model_name = "convbert-base-german-europeana-cased" |
|
|
|
tokenizer = AutoTokenizer.from_pretrained(model_name) |
|
model = AutoModel.from_pretrained(model_name) |
|
``` |
|
|
|
# Huggingface model hub |
|
|
|
All other German Europeana models are available on the [Huggingface model hub](https://huggingface.co/dbmdz). |
|
|
|
# Contact (Bugs, Feedback, Contribution and more) |
|
|
|
For questions about our Europeana BERT, ELECTRA and ConvBERT models just open a new discussion |
|
[here](https://github.com/stefan-it/europeana-bert/discussions) 🤗 |
|
|
|
# Acknowledgments |
|
|
|
Research supported with Cloud TPUs from Google's TensorFlow Research Cloud (TFRC). |
|
Thanks for providing access to the TFRC ❤️ |
|
|
|
Thanks to the generous support from the [Hugging Face](https://huggingface.co/) team, |
|
it is possible to download both cased and uncased models from their S3 storage 🤗 |
