Token Classification
Transformers
Safetensors
English
bert
financial NLP
named entity recognition
sequence labeling
structured extraction
hierarchical taxonomy
XBRL
iXBRL
SEC filings
financial-information-extraction
Instructions to use AAU-NLP/Cal-BERT-SL1000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AAU-NLP/Cal-BERT-SL1000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="AAU-NLP/Cal-BERT-SL1000")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AAU-NLP/Cal-BERT-SL1000") model = AutoModelForTokenClassification.from_pretrained("AAU-NLP/Cal-BERT-SL1000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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