Instructions to use jmmr-8282/email with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jmmr-8282/email with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jmmr-8282/email")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jmmr-8282/email") model = AutoModelForSequenceClassification.from_pretrained("jmmr-8282/email") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a859716c0bd06548fdc1c84c2b4285899090f31ba6f8ca97fd5e07de40be5f99
- Size of remote file:
- 5.2 kB
- SHA256:
- 98a50508f60c9b4d03d1ce0762367dd94594adac9bacc791a56c5179c99428a5
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