Average Model Cost: $0.0023
Number of Runs: 8,740,733
Models by this creator
Kandinsky-2.2 is a multilingual text-to-image latent diffusion model. It takes as input a text description in different languages and generates an image that corresponds to the description. The model utilizes a latent diffusion process to refine and optimize the image generation. It is designed to support multiple languages, making it flexible for a variety of text-to-image applications.
Kandinsky 2.1 is a diffusion model that generates images using text prompts. The model takes in a textual description and uses it to produce an image that corresponds to the given text. It achieves this by infusing the prompt with a series of random walks to generate a diffusion process, which ultimately forms the image. This model builds upon previous versions and improves the overall quality of the generated images.
mGPT is a text generation model based on the GPT architecture. It is a pre-trained model that can generate coherent and contextually relevant text given a prompt. The model uses a transformer-based architecture that incorporates self-attention mechanisms to capture the relationships between words in a sentence. It has been trained on a large corpus of text data and can generate text in a variety of domains, including news articles, product reviews, and social media posts. The model can be fine-tuned on specific tasks or used as is for general text generation purposes.