# Efficient Feature Extraction

SNAC 24kHz is a model for feature extraction, suitable for audio signal processing tasks.

Vision Transformer model based on SigLIP, containing only the image encoder part, employing a global average pooling strategy

A bge-m3 model optimized for English and Russian, featuring a streamlined vocabulary that retains only English and Russian words, reducing the vocabulary size to 21% of the original while maintaining the quality of embeddings for both languages. The total model parameters are 63.3% of the original version.

Hiera is an efficient hierarchical vision Transformer model that excels in image and video tasks with fast runtime

Hiera is a hierarchical vision Transformer model that is fast, powerful, and concise, surpassing existing technologies in image and video tasks while being faster.

Hiera is a hierarchical vision Transformer model that is fast, powerful, and concise, surpassing state-of-the-art performance in a wide range of image and video tasks while significantly improving runtime speed.

Hiera is a hierarchical vision Transformer model that is fast, powerful, and concise, excelling in image and video tasks.

Hiera is a hierarchical vision Transformer model that combines speed, powerful functionality, and minimalist design, significantly surpassing existing technical standards in image and video tasks with outstanding computational efficiency.

Hiera is a hierarchical vision Transformer model that is fast, powerful, and extremely concise. It surpasses current state-of-the-art techniques in a wide range of image and video tasks while achieving significant speed improvements.

An image feature extraction model based on the EfficientNet-B0 architecture, primarily used for astronomical image analysis

A Transformer model pre-trained on English corpus using ELECTRA-like self-supervised approach, suitable for sentence summarization tasks.

Pre-trained CSP-Darknet-53 Mish architecture image classification model based on the ImageNette dataset