This is a LoRA adapter trained based on the Wan2.1-T2V-14B model, specifically designed for text-to-video conversion tasks and providing enhanced capabilities for image generation. This model is trained using the AI Toolkit and requires a specific trigger word 'diddly' to activate image generation.

MultimodalDiffusers

ruSpamNS_big is a classification model for Russian spam messages on Telegram, fine-tuned based on the DeepPavlov/distilrubert-small-cased-conversational model.

Natural Language ProcessingTransformersrussian

A BERTweet-base fine-tuned classification model for identifying spam/bot tweets related to Bitcoin

Natural Language ProcessingTransformers

This is an English spam SMS classification model fine-tuned from the bert-base-uncased model, capable of accurately distinguishing between spam and legitimate SMS messages.

Natural Language ProcessingSafetensorsEnglish

A spam detection model for SMS messages fine-tuned based on the multilingual BERT model, capable of classifying messages as normal or spam

Natural Language ProcessingTransformersMultiple Languages

A fine-tuned Turkish BERT model for spam SMS detection, used to classify Turkish SMS messages as spam or normal.

Natural Language ProcessingTransformers

This is a BERT model fine-tuned for spam detection with a validation accuracy of approximately 99%

Natural Language ProcessingSafetensorsMultiple Languages

A text classification model fine-tuned based on microsoft/Multilingual-MiniLM-L12-H384, used to classify email subjects as spam (SPAM) or non-spam (NOSPAM).

Natural Language ProcessingTransformers

A Twitter/X Platform spam classification model fine-tuned based on xlm-roberta-large, capable of identifying whether tweets are spam

Natural Language ProcessingTransformersEnglish

A Russian spam detection model based on the Deberta architecture, capable of classifying text as spam or non-spam.

Natural Language ProcessingTransformersOther

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

Natural Language ProcessingTransformersEnglish

A BERT fine-tuned SMS classification model for distinguishing spam from non-spam messages.

Natural Language ProcessingTransformersEnglish

A fine-tuned email spam detection model based on distilbert-base-multilingual-cased, designed to identify multilingual spam emails

Natural Language ProcessingTransformers

Multilingual text toxicity detection model supporting 55 languages for identifying harmful or spam content

Natural Language ProcessingTransformersMultiple Languages

A text classification model fine-tuned on RoBERTa, specifically designed to identify spam emails/messages with an accuracy of 99.06%

Natural Language ProcessingTransformersEnglish

A text classification model supporting over 50 languages, suitable for text classification tasks in multilingual environments

Natural Language ProcessingTransformersMultiple Languages

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

Natural Language ProcessingTransformersChinese

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

Natural Language ProcessingTensorflow

This is a BERT-Tiny fine-tuned SMS spam detection model specifically designed to identify spam and legitimate messages.

Natural Language ProcessingJaxMultiple Languages

A DistilBERT-based SMS spam detection model, fine-tuned on the sms_spam dataset, achieving an accuracy of 99.21%

Natural Language ProcessingTransformers