Text Classification
Transformers
Safetensors
English
bert
finance
cbdc
central-bank
financial-nlp
economic-policy
monetary-policy
sentence-classification
discourse-analysis
policy-analysis
centralbank-bert
bis-speeches
text-embeddings-inference
Instructions to use bilalzafar/CBDC-Discourse with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bilalzafar/CBDC-Discourse with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bilalzafar/CBDC-Discourse")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bilalzafar/CBDC-Discourse") model = AutoModelForSequenceClassification.from_pretrained("bilalzafar/CBDC-Discourse") - Notebooks
- Google Colab
- Kaggle
| { | |
| "label2id": { | |
| "Feature": 0, | |
| "Process": 1, | |
| "Risk-Benefit": 2 | |
| }, | |
| "id2label": { | |
| "0": "Feature", | |
| "1": "Process", | |
| "2": "Risk-Benefit" | |
| } | |
| } |