Text Classification
Transformers
Safetensors
English
me2bert
feature-extraction
Moral Foundation Prediction
MFT
Morality
Morality Values
BERTForMoralPrediction
Emotions
Events
https://aclanthology.org/2025.coling-main.638.pdf
custom_code
Instructions to use lorenzozan/ME2-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lorenzozan/ME2-BERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lorenzozan/ME2-BERT", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lorenzozan/ME2-BERT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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- https://aclanthology.org/2025.coling-main.638.pdf
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pipeline_tag: text-classification
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license: mit
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# ME²-BERT: Are Events and Emotions what you need for Moral Foundation Prediction?
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- https://aclanthology.org/2025.coling-main.638.pdf
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pipeline_tag: text-classification
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license: mit
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- text: "I love my wife."
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# ME²-BERT: Are Events and Emotions what you need for Moral Foundation Prediction?
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