Instructions to use samanta-scratch/intent-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use samanta-scratch/intent-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="samanta-scratch/intent-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("samanta-scratch/intent-classifier") model = AutoModelForSequenceClassification.from_pretrained("samanta-scratch/intent-classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 810c38164413971375e01017ab2296faa5869616bf0a91fad927e0066af9fe0c
- Size of remote file:
- 433 MB
- SHA256:
- b19c57cf787c6c8d9e3f735f8121946a5084f4048d3ce98224b1745fdd08f13b
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