Instructions to use wwbproj/empathic_conversations_self_disclosure with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wwbproj/empathic_conversations_self_disclosure with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wwbproj/empathic_conversations_self_disclosure")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wwbproj/empathic_conversations_self_disclosure") model = AutoModelForSequenceClassification.from_pretrained("wwbproj/empathic_conversations_self_disclosure") - Notebooks
- Google Colab
- Kaggle
Empathic Conversations: Self Disclosure
Model owner(s): Ryan Guan, rguan@seas.upenn.edu Associated paper:
Model description
Related models
- wwbproj/empathic_conversations_empathy
- wwbproj/empathic_conversations_emotion
- wwbproj/empathic_conversations_emotional_polarity
- wwbproj/empathic_conversations_dialog_acts
Intended uses & limitations
How to use
Code: https://github.com/wwbp/models/tree/master/neural_model_code/empathic_conversations
Training data
Training procedure
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