Text Classification
Transformers
Safetensors
English
bert
AI
Sentiment
Finance
Central Bank
Tone
Artificial Intelligence
BIS
text-embeddings-inference
Instructions to use bilalzafar/CentralBank-AI-Sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bilalzafar/CentralBank-AI-Sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bilalzafar/CentralBank-AI-Sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bilalzafar/CentralBank-AI-Sentiment") model = AutoModelForSequenceClassification.from_pretrained("bilalzafar/CentralBank-AI-Sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ae9dcce7abda81dd2d5f3602284114af8b8fc6c530f5a77f1aaf3e1fe120e5b
- Size of remote file:
- 5.71 kB
- SHA256:
- fff9b7cad3f7eb344a20816453f7acab11cafebba08a7626736400bee721606f
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