Text Classification
Transformers
Safetensors
English
bert
token-classification
financial NLP
named entity recognition
sequence labeling
structured extraction
hierarchical taxonomy
XBRL
iXBRL
SEC filings
financial-information-extraction
text-embeddings-inference
Instructions to use AAU-NLP/BERT-SL1000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AAU-NLP/BERT-SL1000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AAU-NLP/BERT-SL1000")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("AAU-NLP/BERT-SL1000") model = AutoModelForTokenClassification.from_pretrained("AAU-NLP/BERT-SL1000") - Notebooks
- Google Colab
- Kaggle
Link model to paper and official repository
#1
by nielsr HF Staff - opened
Hi! I'm Niels, part of the community science team at Hugging Face.
I'm opening this PR to improve the model card for BERT-SL1000. I've added a link to the paper HiFi-KPI: A Dataset for Hierarchical KPI Extraction from Earnings Filings and updated the official GitHub repository link. I've also refined the metadata to include the license, library name, and the appropriate pipeline tag for better discoverability.
Please let me know if you have any questions!
rasmus-aau changed pull request status to merged