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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb6e7e6166d6790f619a674aeb5a671c59232b7ddd6176d1331e382ba14c61b0
- Size of remote file:
- 499 MB
- SHA256:
- a6bfa066e6066c08933354d32641dbcf817d406e57ce3e9d7ace774191a2bfb6
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