Instructions to use imrazaa/Imperative_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imrazaa/Imperative_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="imrazaa/Imperative_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("imrazaa/Imperative_classifier") model = AutoModelForSequenceClassification.from_pretrained("imrazaa/Imperative_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76c76019afafa37a74ce21fb229aec8947ee630b6ce174ef06df5a7ea65f2de6
- Size of remote file:
- 711 MB
- SHA256:
- ddcb407235f5f2582ad8770471af69b6900c79d333ab644e0ae2df18f8f1bccb
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