Token Classification
Transformers
Safetensors
English
bert
NER
named-entity-recognition
central-bank
BIS
speeches
finance
economics
monetary policy
Instructions to use bilalzafar/CentralBank-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bilalzafar/CentralBank-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bilalzafar/CentralBank-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("bilalzafar/CentralBank-NER") model = AutoModelForTokenClassification.from_pretrained("bilalzafar/CentralBank-NER") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c6be6b8fef206d8aa9bcbb20e2ff0da04dcbfb31374fc3b261c85a2b2fddeda5
- Size of remote file:
- 5.37 kB
- SHA256:
- 11966853b04ac4839763d771f94783d62dd9ae1f0d540f4f790e3b78f7e325cc
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