DeepSeek-OCR

DeepSeek-V2 is a state-of-the-art Mixture-of-Experts (MoE) language model introduced by DeepSeek-AI, characterized by its economical training and efficient inference capabilities. With a total of 236 billion parameters, of which only 21 billion are active per token, it supports a context length of up to 128K tokens. DeepSeek-V2 employs innovative architectures like Multi-head Latent Attention (MLA) for efficient inference by compressing the Key-Value (KV) cache and DeepSeekMoE for cost-effective training through sparse computation. This model significantly outperforms its predecessor, DeepSeek 67B, by saving 42.5% in training costs, reducing the KV cache by 93.3%, and enhancing generation throughput by 5.76 times. Pretrained on an 8.1 trillion token corpus, DeepSeek-V2 excels in language understanding, coding, and reasoning tasks, making it a top-tier performer among open-source models.

Automatically compress images achieving the highest compression ratio at consistent image quality. Optimage is a simple yet powerful image optimization tool that provides the highest compression ratio at consistent visual quality, implementing many best practices for using images on the web and mobile. It is the first tool to achieve visually lossless compression in a comprehensive set of third-party tests and the new state of the art in image compression. It can resize and convert common image and video formats, and keep the best quality required for professional photography. It is designed to make automatic image optimization accessible and inclusive to everyone. Thousands of people have been successfully using Optimage to optimize their images. Optimage uses novel perceptual metrics and improved encoders to reduce image size by up to 90% without losing visual quality. Optimage provides the highest compression ratio by using advanced image reduction and data compression algorithms.