Instructions to use hamzaMM/questionClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hamzaMM/questionClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hamzaMM/questionClassifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hamzaMM/questionClassifier") model = AutoModelForSequenceClassification.from_pretrained("hamzaMM/questionClassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d3be12d1dfe05650bbfe200df739f659664fd1fee18deecce3d944fed59b3450
- Size of remote file:
- 44.7 MB
- SHA256:
- 4891c08380b79da043d9098186d5128cd3b94963888165dc0c74bb3bb373df9d
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