
# Danish BERT (version 2, uncased) by [Certainly](https://certainly.io/) (previously known as BotXO).

All credit goes to [Certainly](https://certainly.io/) (previously known as BotXO), who developed Danish BERT. For data and training details see their [GitHub repository](https://github.com/certainlyio/nordic_bert) or [this article](https://www.certainly.io/blog/danish-bert-model/). You can also visit their [organization page](https://huggingface.co/Certainly) on Hugging Face.

It is both available in TensorFlow and Pytorch format. 

The original TensorFlow version can be downloaded using [this link](https://www.dropbox.com/s/19cjaoqvv2jicq9/danish_bert_uncased_v2.zip?dl=1).


Here is an example on how to load Danish BERT in PyTorch using the [🤗Transformers](https://github.com/huggingface/transformers) library:



```python
from transformers import AutoTokenizer, AutoModelForPreTraining

tokenizer = AutoTokenizer.from_pretrained("Maltehb/danish-bert-botxo")
model = AutoModelForPreTraining.from_pretrained("Maltehb/danish-bert-botxo")

```

{"language": "da", "license": "cc-by-4.0", "tags": ["danish", "bert", "masked-lm", "Certainly"], "datasets": ["common_crawl", "wikipedia", "dindebat.dk", "hestenettet.dk", "danishOpenSubtitles"], "pipeline_tag": "fill-mask", "widget": [{"text": "K\u00f8benhavn er [MASK] i Danmark."}]}
transformers pytorch tf jax bert token-classification danish masked-lm Certainly fill-mask da dataset:common_crawl dataset:wikipedia dataset:dindebat.dk dataset:hestenettet.dk dataset:danishOpenSubtitles license:cc-by-4.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #tf #jax #bert #token-classification #danish #masked-lm #Certainly #fill-mask #da #dataset-common_crawl #dataset-wikipedia #dataset-dindebat.dk #dataset-hestenettet.dk #dataset-danishOpenSubtitles #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Danish BERT (version 2, uncased) by Certainly (previously known as BotXO).

All credit goes to Certainly (previously known as BotXO), who developed Danish BERT. For data and training details see their GitHub repository or this article. You can also visit their organization page on Hugging Face.

It is both available in TensorFlow and Pytorch format. 

The original TensorFlow version can be downloaded using this link.


Here is an example on how to load Danish BERT in PyTorch using the Transformers library:





# Danish BERT (version 2, uncased) by Certainly (previously known as BotXO).

All credit goes to Certainly (previously known as BotXO), who developed Danish BERT. For data and training details see their GitHub repository or this article. You can also visit their organization page on Hugging Face.

It is both available in TensorFlow and Pytorch format. 

The original TensorFlow version can be downloaded using this link.


Here is an example on how to load Danish BERT in PyTorch using the Transformers library:
TAGS
#transformers #pytorch #tf #jax #bert #token-classification #danish #masked-lm #Certainly #fill-mask #da #dataset-common_crawl #dataset-wikipedia #dataset-dindebat.dk #dataset-hestenettet.dk #dataset-danishOpenSubtitles #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Danish BERT (version 2, uncased) by Certainly (previously known as BotXO).

All credit goes to Certainly (previously known as BotXO), who developed Danish BERT. For data and training details see their GitHub repository or this article. You can also visit their organization page on Hugging Face.

It is both available in TensorFlow and Pytorch format. 

The original TensorFlow version can be downloaded using this link.


Here is an example on how to load Danish BERT in PyTorch using the Transformers library:
passage: TAGS
#transformers #pytorch #tf #jax #bert #token-classification #danish #masked-lm #Certainly #fill-mask #da #dataset-common_crawl #dataset-wikipedia #dataset-dindebat.dk #dataset-hestenettet.dk #dataset-danishOpenSubtitles #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Danish BERT (version 2, uncased) by Certainly (previously known as BotXO).

All credit goes to Certainly (previously known as BotXO), who developed Danish BERT. For data and training details see their GitHub repository or this article. You can also visit their organization page on Hugging Face.

It is both available in TensorFlow and Pytorch format. 

The original TensorFlow version can be downloaded using this link.


Here is an example on how to load Danish BERT in PyTorch using the Transformers library: