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Browse files- README.md +60 -0
- config.json +50 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +1 -0
- tokenizer_config.json +1 -0
- vocab.txt +0 -0
README.md
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---
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language: da
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tags:
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- danish
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- bert
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- masked-lm
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- botxo
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license: cc-by-4.0
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datasets:
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- common_crawl
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- wikipedia
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- dindebat.dk
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- hestenettet.dk
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- danish OpenSubtitles
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pipeline_tag: token-classification
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widget:
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- text: "Jens er en konge og er født i Danmark."
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---
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# Danish BERT (version 2, uncased) by [BotXO.ai](https://www.botxo.ai/) finetuned for Named Entity Recognition on the [DaNE dataset](https://danlp.alexandra.dk/304bd159d5de/datasets/ddt.zip) (Hvingelby et al., 2020) by Malte Højmark-Bertelsen
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All credit goes to [BotXO.ai](https://www.botxo.ai/) who developed Danish BERT. For data and training details see their [GitHub repository](https://github.com/botxo/nordic_bert) or [this article](https://www.botxo.ai/en/blog/danish-bert-model/).
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It is both available in TensorFlow and Pytorch format.
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The original TensorFlow version can be downloaded using [this link](https://www.dropbox.com/s/19cjaoqvv2jicq9/danish_bert_uncased_v2.zip?dl=1).
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Here is an example on how to load Danish BERT in PyTorch using the [🤗Transformers](https://github.com/huggingface/transformers) library:
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```python
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from transformers import AutoTokenizer, AutoModelForTokenClassification
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tokenizer = AutoTokenizer.from_pretrained("Maltehb/danish-bert-botxo-ner-dane")
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model = AutoModelForTokenClassification.from_pretrained("Maltehb/danish-bert-botxo-ner-dane")
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```
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### References
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Danish BERT. (2020). BotXO. https://github.com/botxo/nordic_bert (Original work published 2019)
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Hvingelby, R., Pauli, A. B., Barrett, M., Rosted, C., Lidegaard, L. M., & Søgaard, A. (2020). DaNE: A Named Entity Resource for Danish. Proceedings of the 12th Language Resources and Evaluation Conference, 4597–4604. https://www.aclweb.org/anthology/2020.lrec-1.565
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#### Contact
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For help or further information feel free to connect with the author Malte Højmark-Bertelsen on [[email protected]](mailto:[email protected]?subject=[GitHub]%20DanishBERTUncasedNER) or any of the following platforms:
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[<img align="left" alt="MalteHB | Twitter" width="22px" src="https://cdn.jsdelivr.net/npm/simple-icons@v3/icons/twitter.svg" />][twitter]
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[<img align="left" alt="MalteHB | LinkedIn" width="22px" src="https://cdn.jsdelivr.net/npm/simple-icons@v3/icons/linkedin.svg" />][linkedin]
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[<img align="left" alt="MalteHB | Instagram" width="22px" src="https://cdn.jsdelivr.net/npm/simple-icons@v3/icons/instagram.svg" />][instagram]
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<br />
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</details>
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[twitter]: https://twitter.com/malteH_B
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[instagram]: https://www.instagram.com/maltemusen/
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[linkedin]: https://www.linkedin.com/in/malte-h%C3%B8jmark-bertelsen-9a618017b/
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config.json
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{
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"architectures": [
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"BertForTokenClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"directionality": "bidi",
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "B-PER",
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"1": "I-PER",
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"2": "B-LOC",
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"3": "I-LOC",
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"4": "B-ORG",
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"5": "I-ORG",
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"6": "O",
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"7": "LABEL_7",
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"8": "LABEL_8",
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"9": "LABEL_9"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2,
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"LABEL_3": 3,
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"LABEL_4": 4,
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"LABEL_5": 5,
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"LABEL_6": 6,
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"LABEL_7": 7,
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"LABEL_8": 8,
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"LABEL_9": 9
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"pooler_fc_size": 768,
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"pooler_num_attention_heads": 12,
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"pooler_num_fc_layers": 3,
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"pooler_size_per_head": 128,
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"pooler_type": "first_token_transform",
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"type_vocab_size": 2,
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"vocab_size": 32000
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:dc35edd66a00d96a8195e805fda4b35008c5a3ae9947bff8b9e9d8cb1fa3767e
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size 440224266
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special_tokens_map.json
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{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}
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tokenizer_config.json
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{"do_lower_case": true, "strip_accents": false}
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vocab.txt
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