Instructions to use roshana1s/spam-message-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roshana1s/spam-message-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="roshana1s/spam-message-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("roshana1s/spam-message-classifier") model = AutoModelForSequenceClassification.from_pretrained("roshana1s/spam-message-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86355269543bc08a39a5125f106de430c3ac11b6e959fb21e92d7c333edaf07b
- Size of remote file:
- 5.78 kB
- SHA256:
- 68757fe8b6ac23230c4a0c1ae0830e26d79ffc45a4ae86ba025a409adc75628e
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