Text Classification
Transformers
Safetensors
modernbert
Generated from Trainer
text-embeddings-inference
Instructions to use Umranz/Email-Spam-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Umranz/Email-Spam-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Umranz/Email-Spam-Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Umranz/Email-Spam-Classifier") model = AutoModelForSequenceClassification.from_pretrained("Umranz/Email-Spam-Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7466a33ad843a542c75611f2e05c63b4adc799d821b5656e731a47b5bb0e040
- Size of remote file:
- 5.2 kB
- SHA256:
- 574f0baac40c9fd9e4f439b21327fd4e5a480e697f89deb8a2bfb8720fd1caf4
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