# Transformer Models

SeedVR is an innovative diffusion transformer model specifically created for addressing real-world video restoration tasks. Its unique shifted window attention mechanism allows it to efficiently process video sequences of arbitrary length and resolution. The design of SeedVR has significantly enhanced both its generative capabilities and sampling efficiency, outperforming traditional diffusion models in both synthesis and real-world benchmarks. Moreover, SeedVR incorporates modern practices such as causal video autoencoders, mixed image and video training, and progressive training, further enhancing its competitiveness in the field of video restoration. As a cutting-edge video restoration technology, SeedVR provides video content creators and post-production professionals with a powerful tool that can significantly improve video quality, especially when working with low-quality or damaged video materials.

Transformer Explainer is an online visualization tool dedicated to helping users thoroughly understand Transformer models. It graphically displays various components of the Transformer model, including the self-attention mechanism and feedforward networks, allowing users to visually see the flow and processing of data within the model. This tool holds significant importance in the education and research fields, aiding students and researchers in better comprehending advanced technologies in natural language processing.

CS25 is a course offered by Stanford University that delves into Transformer models, a revolutionary architecture in deep learning. The course invites leading experts in the Transformer research field to discuss cutting-edge advancements, ranging from LLM architectures like GPT and Gemini to creative applications such as DALL-E and Sora. CS25 has become one of the most popular and exciting workshop courses at Stanford.