Instructions to use satish860/sms_detection_algorithm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use satish860/sms_detection_algorithm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="satish860/sms_detection_algorithm")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("satish860/sms_detection_algorithm") model = AutoModelForSequenceClassification.from_pretrained("satish860/sms_detection_algorithm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec50a0e002e69dff4775362b4e42c2b674aa8e7eae3c12d2e6b647d7c9834dee
- Size of remote file:
- 268 MB
- SHA256:
- 2056cd1dcb79806314b2965d85ec8262f8e889b389fb7fd48e0d4abdbb08da0f
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