T5Gemma is a family of lightweight encoder-decoder research models launched by Google. By adapting the pre-trained decoder-only model to an encoder-decoder architecture, it achieves a better balance between quality and efficiency. This model supports various generation and discrimination tasks and is suitable for deployment in resource-constrained environments.

Natural Language ProcessingTransformers

T5Gemma is a lightweight encoder-decoder research model family launched by Google. By adapting the decoder-only pre-trained model to the encoder-decoder architecture, it achieves a good balance between quality and efficiency. This model is suitable for various generation and discrimination tasks and supports English processing.

Natural Language ProcessingTransformers

T5Gemma is a family of lightweight and powerful encoder-decoder research models launched by Google, suitable for a variety of generation and discrimination tasks.

Natural Language ProcessingTransformers

A Turkish sentiment analysis model based on the BERT architecture, specifically designed for four sentiment classifications of social media texts: racism, provocation, neutrality, and gender discrimination, with an accuracy rate of 93.7%.

Natural Language ProcessingSafetensorsOther

Based on the BERTweet-large model, a gender discrimination detection model fine-tuned on the Explainable Online Sexism Detection (EDOS) dataset, specifically designed to identify gender discrimination content in tweets. It achieves an accuracy of 89.72% and an F1 score of 86.13% on the test set.

Natural Language ProcessingTransformersEnglish