# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("csariyildiz/enron_spam_bert_base")
model = AutoModelForSequenceClassification.from_pretrained("csariyildiz/enron_spam_bert_base")Quick Links
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Finetuned BERT For Spam Detection On Enron Dataset
- Labels: Ham 0, Spam 1
- Accuracy: 0.9964012595591543
- Dataset contains a total of 17.171 spam and 16.545 non-spam ("ham") e-mail messages (33.716 e-mails total).
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="csariyildiz/enron_spam_bert_base")