Instructions to use acmc/satisfaction_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use acmc/satisfaction_model with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("acmc/satisfaction_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6dcb0c2f8e887c5f4d23e96c329a22fc31fd58cafe6d3d6f4859a2e85b48d691
- Size of remote file:
- 1.13 GB
- SHA256:
- 5a62677a031075fbc6ae72abb88a5d6caaac71e36c0408d571b7ea378ab5d757
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