Instructions to use nlpaueb/sec-bert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpaueb/sec-bert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nlpaueb/sec-bert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("nlpaueb/sec-bert-base") model = AutoModelForPreTraining.from_pretrained("nlpaueb/sec-bert-base") - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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## Publication
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The model has been officially released with the following article:<br>
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"FiNER: Financial Numeric Entity Recognition for XBRL Tagging".<br>
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Lefteris Loukas, Manos Fergadiotis, Ilias Chalkidis, Eirini Spyropoulou, Prodromos Malakasiotis, Ion Androutsopoulos and George Paliouras.<br>
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In the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) (Long Papers), Dublin, Republic of Ireland, May 22 - 27, 2022.
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## About Us
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[AUEB's Natural Language Processing Group](http://nlp.cs.aueb.gr) develops algorithms, models, and systems that allow computers to process and generate natural language texts.
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## Publication
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The model has been officially released with the following article:<br>
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**"FiNER: Financial Numeric Entity Recognition for XBRL Tagging"**.<br>
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Lefteris Loukas, Manos Fergadiotis, Ilias Chalkidis, Eirini Spyropoulou, Prodromos Malakasiotis, Ion Androutsopoulos and George Paliouras.<br>
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In the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) (Long Papers), Dublin, Republic of Ireland, May 22 - 27, 2022.
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```
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@inproceedings{loukas-etal-2022-finer,
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title = "{FiNER}: Financial Numeric Entity Recognition for {XBRL} Tagging",
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author = "Loukas, Lefteris and
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Fergadiotis, Manos and
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Chalkidis, Ilias and
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Spyropoulou, Eirini and
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Malakasiotis, Prodromos and
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Androutsopoulos, Ion and
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Paliouras George",
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booktitle = "60th Annual Meeting of the Association for Computational Linguistics",
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month = may,
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year = "2022",
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publisher = "Association for Computational Linguistics",
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}
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```
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## About Us
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[AUEB's Natural Language Processing Group](http://nlp.cs.aueb.gr) develops algorithms, models, and systems that allow computers to process and generate natural language texts.
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