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
| { | |
| "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 | |
| } | |
| } |