Text Classification
Transformers
Safetensors
English
bert
CBDC
Central Bank Digital Currencies
Central Bank Digital Currency
Central Bank
Stance Classification
Finance
NLP
Finance NLP
BERT
Transformers
Digital Currency
text-embeddings-inference
Instructions to use bilalzafar/CBDC-Stance with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bilalzafar/CBDC-Stance with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bilalzafar/CBDC-Stance")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bilalzafar/CBDC-Stance") model = AutoModelForSequenceClassification.from_pretrained("bilalzafar/CBDC-Stance", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from bilalzafar/CBDC-Stance: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/bilalzafar/CBDC-Stance/resolve/main/tokenizer.json
- Command line
-
hf download hf://bilalzafar/CBDC-Stance/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/bilalzafar/CBDC-Stance/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.