Instructions to use imrazaa/Imperative_classifier_batch_8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use imrazaa/Imperative_classifier_batch_8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="imrazaa/Imperative_classifier_batch_8")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("imrazaa/Imperative_classifier_batch_8") model = AutoModelForSequenceClassification.from_pretrained("imrazaa/Imperative_classifier_batch_8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1bb447eec873e513a8b2e66a6eb2e10808122f8322e167d827d727a33effc291
- Size of remote file:
- 711 MB
- SHA256:
- c2717fc1f936433f44cbb080f644e4093045ba315a149d466e8d3bb8d2fc548b
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