Instructions to use Goodmotion/spam-mail-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Goodmotion/spam-mail-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Goodmotion/spam-mail-classifier")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Goodmotion/spam-mail-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d5fdf821bbd17bce3b11b7702814f271ad2359b9784d42b9ee1b5b96f73d5ce
- Size of remote file:
- 769 Bytes
- SHA256:
- e1f5d888b080781be08c900cb8478a9024c698e80161535b4112b298674d6539
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.