Average Model Cost: $0.0007
Number of Runs: 5,498,450
Models by this creator
The stable-diffusion-v1-5 model is a deep learning model that allows for the stable diffusion of text-to-image generation. It is trained on a large dataset of text and image pairs to learn the complex relationship between the two modalities. The model can take in a text prompt and generate a corresponding image that matches the description. It achieves this by utilizing deep learning techniques such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs). The stable-diffusion-v1-5 model is designed for applications such as image synthesis, creative design, and content generation.
Stable Diffusion Inpainting is a latent text-to-image diffusion model that can generate photo-realistic images based on text inputs. It has the additional capability of inpainting images using a mask. The model was trained using LAION-2B(en) dataset, along with other subsets, and a ViT-L/14 text encoder. It has some limitations, such as not achieving perfect photorealism and difficulty rendering complex compositions. The model is intended for research purposes and should not be used for malicious or harmful content generation. It may also exhibit biases towards white and Western cultures and has limitations when generating non-English prompts. The model card provides information on training data, evaluation results, and environmental impact.