Text Classification
Transformers
Safetensors
English
distilbert
text-generation-inference
spam-detection
nlp
binary-classification
text-embeddings-inference
Instructions to use kenbaker-gif/Email_Spam_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kenbaker-gif/Email_Spam_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kenbaker-gif/Email_Spam_Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kenbaker-gif/Email_Spam_Classifier") model = AutoModelForSequenceClassification.from_pretrained("kenbaker-gif/Email_Spam_Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9fde1b137aa70eb8fb426904c921f0b85c054637a0be8a6cb3df83cc6f358aa4
- Size of remote file:
- 5.71 kB
- SHA256:
- 4798b0cd90f566c5ebaf3805db0a201ea4c11997724656839e13030f069dd873
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