Text Classification
Transformers
Safetensors
English
distilbert
ethics
ai-ethics
education
Eval Results (legacy)
text-embeddings-inference
Instructions to use nexageapps/EthicsBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nexageapps/EthicsBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nexageapps/EthicsBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nexageapps/EthicsBERT") model = AutoModelForSequenceClassification.from_pretrained("nexageapps/EthicsBERT") - Notebooks
- Google Colab
- Kaggle
File size: 446 Bytes
7e2ccc4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"id2label": {
"0": "Agency",
"1": "AI Governance",
"2": "Bias",
"3": "Consciousness",
"4": "Ethical Reasoning",
"5": "Explainability",
"6": "Fairness",
"7": "Intelligence",
"8": "Privacy"
},
"label2id": {
"Agency": 0,
"AI Governance": 1,
"Bias": 2,
"Consciousness": 3,
"Ethical Reasoning": 4,
"Explainability": 5,
"Fairness": 6,
"Intelligence": 7,
"Privacy": 8
}
} |