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Riffusion is a neural network, designed by Seth Forsgren and Hayk Martiros, that generates music using images of sound rather than audio. [1] It was created as a fine-tuning of Stable Diffusion , an existing open-source model for generating images from text prompts, on spectrograms . [ 1 ]
The model is insufficiently trained to understand human limbs and faces due to the lack of representative features in the database, and prompting the model to generate images of such type can confound the model. [37] Stable Diffusion XL (SDXL) version 1.0, released in July 2023, introduced native 1024x1024 resolution and improved generation for ...
The model was made available on December 15, 2022, with the code also freely available on GitHub. [42] It is one of many models derived from Stable Diffusion. [44] Riffusion is classified within a subset of AI text-to-music generators. In December 2022, Mubert [46] similarly used Stable Diffusion to turn descriptive text into music loops. In ...
Josh Allen got the win and a warning from referee Bill Vinovich on Sunday in Buffalo's wild-card win over the Denver Broncos. With the Bills leading early in the third quarter, Buffalo ran a pass ...
AUTOMATIC1111 Stable Diffusion Web UI (SD WebUI, A1111, or Automatic1111 [3]) is an open source generative artificial intelligence program that allows users to generate images from a text prompt. [4] It uses Stable Diffusion as the base model for its image capabilities together with a large set of extensions and features to customize its output.
In 2023, the US imported $5.69 billion of beer and $4.81 billion of alcohol from Mexico, according to International Trade Administration data. When combined, the two categories were the 10th ...
Even after weeks of close analysis, Super Bowl 59 still found a way to surprise many, as the Eagles secured a rare knockout of the Chiefs.
DALL-E 2 is a 3.5-billion cascaded diffusion model that generates images from text by "inverting the CLIP image encoder", the technique which they termed "unCLIP". The unCLIP method contains 4 models: a CLIP image encoder, a CLIP text encoder, an image decoder, and a "prior" model (which can be a diffusion model, or an autoregressive model).