# Spam Detection

A DistilBERT-based SMS spam classification model, fine-tuned on the sms_spam dataset, used to identify spam messages.

RoBERTa-base is a pre-trained language model based on the Transformer architecture, developed by Facebook AI, suitable for various natural language processing tasks.

This is a binary classification model trained using AutoTrain, specifically designed to distinguish between spam and non-spam emails.

This is a model based on the Keras framework, with unspecified functionality, possibly used for image classification or spam detection tasks

A text classification model fine-tuned on SMS spam datasets based on the roberta-base model, used to detect whether a message is spam.