Instructions to use paragon-analytics/bert_empathy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paragon-analytics/bert_empathy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="paragon-analytics/bert_empathy")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("paragon-analytics/bert_empathy") model = AutoModelForSequenceClassification.from_pretrained("paragon-analytics/bert_empathy") - Notebooks
- Google Colab
- Kaggle
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README.md
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license: "mit"
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This model takes text (up to a few sentences) and predicts to what extent it contains
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Example classification:
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license: "mit"
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This is a fine-tuned RoBERTa model that takes text (up to a few sentences) and predicts to what extent it contains empathic language.
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Example classification:
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