Instructions to use twigs/cwi-regressor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use twigs/cwi-regressor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="twigs/cwi-regressor")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("twigs/cwi-regressor") model = AutoModelForSequenceClassification.from_pretrained("twigs/cwi-regressor") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94a5fcc1eb7795ec3ed026c75bfc98ac8463a36b4b4c82f95c2bbfa88283fce1
- Size of remote file:
- 268 MB
- SHA256:
- 4139499d9178b9a36c6c82707e8326132796f2c473832cc537f90488295d9cd7
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