
# 🤗 + 📚 dbmdz ConvBERT model

In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources a German Europeana ConvBERT model 🎉

# 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 = "dbmdz/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 🤗
{"language": "de", "license": "mit", "tags": ["historic german"]}
transformers pytorch tf safetensors convbert feature-extraction historic german de license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #tf #safetensors #convbert #feature-extraction #historic german #de #license-mit #endpoints_compatible #region-us 


#  +  dbmdz ConvBERT model

In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources a German Europeana ConvBERT model 

# German Europeana ConvBERT

We use the open source Europeana newspapers
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.

## Results

For results on Historic NER, please refer to this repository.

## Usage

With Transformers >= 4.3 our German Europeana ConvBERT model can be loaded like:



# Huggingface model hub

All other German Europeana models are available on the Huggingface model hub.

# Contact (Bugs, Feedback, Contribution and more)

For questions about our Europeana BERT, ELECTRA and ConvBERT models just open a new discussion
here 

# 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 team,
it is possible to download both cased and uncased models from their S3 storage 
#  +  dbmdz ConvBERT model

In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources a German Europeana ConvBERT model # German Europeana ConvBERT

We use the open source Europeana newspapers
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. ## Results

For results on Historic NER, please refer to this repository. ## Usage

With Transformers >= 4.3 our German Europeana ConvBERT model can be loaded like: # Huggingface model hub

All other German Europeana models are available on the Huggingface model hub. # Contact (Bugs, Feedback, Contribution and more)

For questions about our Europeana BERT, ELECTRA and ConvBERT models just open a new discussion
here # 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 team,
it is possible to download both cased and uncased models from their S3 storage
TAGS
#transformers #pytorch #tf #safetensors #convbert #feature-extraction #historic german #de #license-mit #endpoints_compatible #region-us 
 #  +  dbmdz ConvBERT model

In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources a German Europeana ConvBERT model # German Europeana ConvBERT

We use the open source Europeana newspapers
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. ## Results

For results on Historic NER, please refer to this repository. ## Usage

With Transformers >= 4.3 our German Europeana ConvBERT model can be loaded like: # Huggingface model hub

All other German Europeana models are available on the Huggingface model hub. # Contact (Bugs, Feedback, Contribution and more)

For questions about our Europeana BERT, ELECTRA and ConvBERT models just open a new discussion
here # 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 team,
it is possible to download both cased and uncased models from their S3 storage
passage: TAGS
#transformers #pytorch #tf #safetensors #convbert #feature-extraction #historic german #de #license-mit #endpoints_compatible #region-us 
#  +  dbmdz ConvBERT model

In this repository the MDZ Digital Library team (dbmdz) at the Bavarian State
Library open sources a German Europeana ConvBERT model# German Europeana ConvBERT

We use the open source Europeana newspapers
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.## Results

For results on Historic NER, please refer to this repository.## Usage

With Transformers >= 4.3 our German Europeana ConvBERT model can be loaded like:# Huggingface model hub

All other German Europeana models are available on the Huggingface model hub.# Contact (Bugs, Feedback, Contribution and more)

For questions about our Europeana BERT, ELECTRA and ConvBERT models just open a new discussion
here# 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 team,
it is possible to download both cased and uncased models from their S3 storage