Instructions to use classla/bcms-bertic-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use classla/bcms-bertic-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="classla/bcms-bertic-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("classla/bcms-bertic-ner") model = AutoModelForTokenClassification.from_pretrained("classla/bcms-bertic-ner") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -30,8 +30,8 @@ If you use this fine-tuned model, please cite the following paper:
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```
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@inproceedings{ljubesic-lauc-2021-bertic,
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title = "{BERT}i{\
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author = "Ljube{\
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booktitle = "Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing",
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month = apr,
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year = "2021",
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```
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@inproceedings{ljubesic-lauc-2021-bertic,
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title = "{BERT}i{\'c} - The Transformer Language Model for {B}osnian, {C}roatian, {M}ontenegrin and {S}erbian",
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author = "Ljube{\v{s}}i{\'c}, Nikola and Lauc, Davor",
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booktitle = "Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing",
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month = apr,
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year = "2021",
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