Instructions to use Abhibeats95/question_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abhibeats95/question_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Abhibeats95/question_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Abhibeats95/question_classification") model = AutoModelForSequenceClassification.from_pretrained("Abhibeats95/question_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d14d90fe7c30264595fe4ee1732efa0d0b31a8d60ab52914bf1315b79bedd379
- Size of remote file:
- 4.6 kB
- SHA256:
- cc7f62bb1346709b83c35739bc14f8c234adedac9ccfed1fd56837f59bb80bc4
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