ucirvine/sms_spam
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How to use JavicR22/SpamVision with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="JavicR22/SpamVision") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("JavicR22/SpamVision")
model = AutoModelForSequenceClassification.from_pretrained("JavicR22/SpamVision")SpamVision BETO is a fine-tuned BERT model for Spanish language specifically designed to detect spam SMS messages with high accuracy. Built on top of the BETO (BERT trained on Spanish corpus), this model achieves 96.2% accuracy in distinguishing between legitimate messages and spam.
This model is part of the SpamVision project, a hybrid AI system that combines rule-based filtering (AFD) with deep learning for maximum spam detection performance.
dccuchile/bert-base-spanish-wwm-casedBase model
dccuchile/bert-base-spanish-wwm-cased