To make the text more reader-friendly and easier to understand for a non-expert, I will break down the description into simpler terms without losing the essence of the content.
Heal description: Stock photo with a realistic photographic look and idea of a digital data 3D object floating in the air. The artwork has a perfect arrangement with a gradient background of bright rainbow colors and surreal collage style. It’s designed in a realistic way.
What is the connection to the stock photo? Quite literally, it refers to a photorealistic visual representation of a 3D object in the air with an isolated, blurred gradient background and bright rainbow colors. It’s a digital artwork that features a surreal collage-style and avant-garde aesthetic.
Now, the 20 stages involve these parameters: a double exposure photo illustration, sense of realism, photorealistic concept, virtual projection, 3D rendered floating digital data network symbol, excellent composition, isolated on a blurred gradient mesh background in bright rainbow colors, and digital artwork with a surreal collage-style, avant-garde aesthetic, and realistic style. The result is an eerie and captivating design with triangles and a backdrop for designs, created using a vector illustration and a vector art illustration, isolated on a blurred gradient mesh background in bright rainbow colors, with a surreal collage style, avant-garde aesthetic, and realistic style. What’s the connection to the stock photo?
Regarding the geometry and the connections between the triangles, connected purple and blue vertical backgrounds, the texture, and the backdrop for designs. The triangles’ connection has a name, but it’s not explicitly mentioned. It’s designed as a vector illustration and a vector art illustration isolated on a blurred gradient mesh background in bright rainbow colors, with a surreal collage style, avant-garde aesthetic, and realistic style. What’s the connection to the stock photo?
About functioninghe process builds on a formula called SAM (Scaled Autoregressive Model) using an advanced technique called reversible diffusion, based on a previous version201 V1.10.1, which I’ll call “v1” for simplicity. This uses a different model training method called Latent Diffusion, separates the sampling and autoregressive decoder, and enables better handling of very high-resolution images. To understand it better, it’s like saying the model uses the same maximum quality(768×768) and manual decoding, separate jobs scheduled alongside each other, creating the images instead of the sequential sampler.
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