Average Model Cost: $0.0322
Number of Runs: 26,418
Models by this creator
DALL·E Mega is a text-to-image model that generates high-resolution images from text descriptions. It is a more advanced version of the original DALL·E model and produces better results. However, it is recommended to use the min-dalle model instead, as it is considered superior.
The latent-diffusion model is a deep learning approach that can generate high-resolution images from given text descriptions. It uses a diffusion process to progressively refine a latent code representation of the image, achieving better image quality and flexibility compared to traditional generative models like GANs. The model is trained on a large dataset of text-image pairs and can be fine-tuned for specific domains or styles of images.
The real-esrgan-nitroviper model is an image-to-image deep learning model that aims to enhance the quality of images. However, it is currently broken and should not be used. It is only publicly available for API usage and debugging purposes.
GLID-3 is a model that generates images quickly. It is a text-to-image model that can create images based on textual descriptions. The model is designed to be fast and efficient, making it suitable for real-time applications and systems with limited computational resources.