Instructions to use darshandugar/MailClassifier-DistilBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use darshandugar/MailClassifier-DistilBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="darshandugar/MailClassifier-DistilBERT")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("darshandugar/MailClassifier-DistilBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01a020e3356ac1d04b6a8ba722696eefc7b6a92e52423cafa8fdaccca6ec256a
- Size of remote file:
- 268 MB
- SHA256:
- 7fac6419e77780fe02afc5b3a6244b1032c4d820af8e2972200e4fd803c6085e
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