# Sliding Window Attention

A 1.8B parameter base language model trained by H2O.ai, based on an improved Llama 2 architecture with 16K context length support

Mistral-7B-Instruct-v0.1 is a version of the Mistral-7B-v0.1 generative text model fine-tuned with various public dialogue datasets for instruction following.

NAT-Base is a Vision Transformer model trained on ImageNet-1K, which uses the neighborhood attention mechanism for image classification.

NAT-Small is a hierarchical vision transformer based on neighborhood attention, designed for image classification tasks.

NAT-Mini is a lightweight vision Transformer model based on neighborhood attention mechanism, designed for ImageNet image classification tasks

DiNAT-Mini is a hierarchical vision Transformer model based on neighborhood attention mechanism, specifically designed for image classification tasks.

Vision model based on Swin Transformer architecture, fine-tuned specifically for brain tumor image analysis

A Spanish long-document processing model developed based on RoBERTa checkpoints, supporting sequence lengths of up to 4096 tokens