Text Classification
Transformers
Safetensors
PyTorch
ml-lab
spam-detection
distilbert
Eval Results (legacy)
Instructions to use shalev396/email-spam-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shalev396/email-spam-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shalev396/email-spam-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shalev396/email-spam-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from shalev396/email-spam-classifier: direct link, hf CLI and curl.
- Browser
- Download file 711 kB
-
https://huggingface.co/shalev396/email-spam-classifier/resolve/main/tokenizer.json
- Command line
-
hf download hf://shalev396/email-spam-classifier/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/shalev396/email-spam-classifier/resolve/main/tokenizer.json
711 kB
File too large to display, you can check the raw version instead.