Instructions to use dima806/email-spam-detection-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/email-spam-detection-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dima806/email-spam-detection-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dima806/email-spam-detection-roberta") model = AutoModelForSequenceClassification.from_pretrained("dima806/email-spam-detection-roberta") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43ac35995aacfe1557aeac8be9bb162f12354004ec59b28b658f9d8f46e34070
- Size of remote file:
- 4.03 kB
- SHA256:
- 443feaf6cd776e848e4a576a204d94c5ad9bae00cb2c7fd053ca546f45413488
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