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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("nlpaueb/sec-bert-base") model = AutoModelForPreTraining.from_pretrained("nlpaueb/sec-bert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -183,7 +183,7 @@ model = AutoModel.from_pretrained("nlpaueb/sec-bert-base")
|
|
| 183 |
## Publication
|
| 184 |
|
| 185 |
The model has been officially released with the following article:<br>
|
| 186 |
-
**"FiNER: Financial Numeric Entity Recognition for XBRL Tagging"**<br>
|
| 187 |
Lefteris Loukas, Manos Fergadiotis, Ilias Chalkidis, Eirini Spyropoulou, Prodromos Malakasiotis, Ion Androutsopoulos and George Paliouras<br>
|
| 188 |
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
|
| 189 |
|
|
|
|
| 183 |
## Publication
|
| 184 |
|
| 185 |
The model has been officially released with the following article:<br>
|
| 186 |
+
**["FiNER: Financial Numeric Entity Recognition for XBRL Tagging"](https://arxiv.org/abs/2203.06482)**<br>
|
| 187 |
Lefteris Loukas, Manos Fergadiotis, Ilias Chalkidis, Eirini Spyropoulou, Prodromos Malakasiotis, Ion Androutsopoulos and George Paliouras<br>
|
| 188 |
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
|
| 189 |
|