Instructions to use StanBienaives/question_classification_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use StanBienaives/question_classification_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="StanBienaives/question_classification_test")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("StanBienaives/question_classification_test") model = AutoModelForSequenceClassification.from_pretrained("StanBienaives/question_classification_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e9bf57239ac0e7efce56db9f242735cffc3b398ec342eb19749e330cce6ae17
- Size of remote file:
- 553 MB
- SHA256:
- a19d03b67dcfda589b03d1c59a169a3f0c35f16d2a24ac8aaeb01c83150f7f56
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