Showing 3 open source projects for "jpeg image decoder"

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  • 1
    OpenAI DALL·E AsyncImage SwiftUI

    OpenAI DALL·E AsyncImage SwiftUI

    OpenAI swift async text to image for SwiftUI app using OpenAI

    ...It uses diffusion models for both the model's prior (which produces an image embedding given a text caption) and the decoder that generates the final image. In machine learning, diffusion models, also known as diffusion probabilistic models, are a class of latent variable models. They are Markov chains trained using variational inference. The goal of diffusion models is to learn the latent structure of a dataset by modeling the way in which data points diffuse through the latent space.
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  • 2
    DALL-E 2 - Pytorch

    DALL-E 2 - Pytorch

    Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis

    ...To train CLIP, you can either use x-clip package, or join the LAION discord, where a lot of replication efforts are already underway. Then, you will need to train the decoder, which learns to generate images based on the image embedding coming from the trained CLIP.
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  • 3
    Karlo

    Karlo

    Text-conditional image generation model based on OpenAI's unCLIP

    Karlo is a text-conditional image generation model based on OpenAI's unCLIP architecture with the improvement over the standard super-resolution model from 64px to 256px, recovering high-frequency details only in the small number of denoising steps. We train all components from scratch on 115M image-text pairs including COYO-100M, CC3M, and CC12M. In the case of Prior and Decoder, we use ViT-L/14 provided by OpenAI’s CLIP repository.
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