Average Model Cost: $0.0267

Number of Runs: 71,586

Models by this creator

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JoJoGAN is a deep learning model that is designed for one-shot face stylization. It takes an input image of a person's face and generates a stylized version of the face based on a given reference image. The model achieves this by learning a mapping between the input and reference images through a generative adversarial network (GAN). It is trained using a combination of a perceptual loss and an identity loss, which helps to ensure that the generated faces are both visually appealing and faithful to the individual's identity. The model is able to capture a wide range of styles, making it a versatile tool for artistic applications and image editing.

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The model, gans-n-roses, is an image-to-image translation model that can convert images or videos of a person's face into an anime style. It uses generative adversarial networks (GANs) to learn the mapping between real faces and their anime counterparts. This model can be used for various applications such as creating personalized avatar images or adding anime-style effects to videos.

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