SDXL TurboSDXL Turbo is a new text-to-image generation model that utilizes a distillation technique called Adversarial Diffusion Distillation (ADD), allowing it to create image outputs in a single step. This real-time model maintains high sampling fidelity while significantly reducing the required step count from 50 to just one, resulting in improved efficiency.The distillation technique used in SDXL Turbo combines adversarial training and score distillation, as detailed in the research paper provided by Stability AI. This technique enables the model to generate image outputs with high quality and eliminates common issues such as artifacts and blurriness that may occur with other distillation methods.In performance comparisons with other diffusion models like StyleGAN-T++, OpenMUSE, IF-XL, SDXL, and LCM-XL, SDXL Turbo outperformed these models in terms of following the given prompt and image quality, even surpassing a 4-step configuration of LCM-XL with just a single step and a 50-step configuration of SDXL with only 4 steps. Its compatibility with Stability AI's image editing platform, Clipdrop, provides users with an opportunity to explore and test the capabilities of this real-time image generation model.Please note that SDXL Turbo is currently not intended for commercial use, and if you're interested in using this model for commercial purposes, you should contact Stability AI for further information.
View SDXL TurboCody is an AI code assistant that is designed to help developers write code and find answers to their coding questions. It utilizes Sourcegraph's code graph and Large Language Models (LLMs) to provide assistance. Experimental completions: Cody can provide suggestions as you code.Cody can be used in various ways, such as through the Cody app, as an editor extension for VS Code and JetBrains, or by connecting it to a Sourcegraph enterprise instance. Developers can chat with Cody in the editor or the Sourcegraph sidebar to ask questions or provide fixup instructions. Cody will provide responses based on the code files it has read, and if it gives incorrect answers, feedback can be shared to help improve its accuracy.Overall, Cody aims to reduce toil and enhance developers' productivity by providing reliable code assistance and answering coding queries based on its extensive knowledge base.
