The model has been tested with Python 3.10, Torch 2.6.0, and Transformers 4.57.1, and has been evaluated on several benchmarks, including CVTG-2K, LongText-Bench, DPG-Bench, GenEval, OneIG-EN, and OneIG-ZN. It has shown strong performance on these benchmarks, demonstrating its ability to generate high-quality text-to-image outputs. The model's architecture is designed to be efficient and scalable, making it suitable for a wide range of applications.
Ovis-Image has been merged into several popular repositories, including stable-diffusion.cpp, diffusers, and ComfyUI. It has also been demonstrated to be effective in generating high-quality text-to-image outputs, with examples showcasing its capabilities. The model is designed to be easy to use, with a simple and intuitive interface, and is suitable for a wide range of applications, including text-to-image generation, image editing, and more.
