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...s [[DALL-E 2]], an image generation model[1]. Generative models, including Diffusion Models, GANs, Variational Autoencoders (VAEs), and Flow-based models, are d ...s. Towards Data Science. https://towardsdatascience.com/beginners-guide-to-diffusion-models-8c3435ccb4ae</ref>

[[File:1. Stable Diffusion developer adoption.png|thumb|Figure 1. Stable Diffusion developer adoption. Source: A16S and GitHub.]] ...ld. https://www.pcworld.com/article/916785/creating-ai-art-local-pc-stable-diffusion.html</ref>

...wing a user's natural language [[prompt]] (figure 1). According to OpenAI, diffusion "starts with a pattern of random dots and gradually alters that pattern tow #Decoder Diffusion model (unCLIP): Generates and image by convert the CLIP image embedding;

| '''[[DM]]''' || || [[Diffusion model]] | '''[[hLDA]]''' || || [[Hierarchical Latent Dirichlet allocation]]

...”">Witteveen, S and Andrews, M (2022). Investigating Prompt Engineering in Diffusion Models. arXiv:2211.15462v1 https://arxiv.org/pdf/2211.15462.pdf</ref> ...r writing input prompts have emerged, such as the "Traveler's Guide to the Latent Space," which recommends specific prompt templates such as [Medium][Subject