**This may change from time to time so please look at the notebook on how to properly get the model. This should complete the first step of getting ready to fully run the DSD Notebook. Drag the sd-v1-4.ckpt to this folder and wait for it to upload to your Google Drive.Inside the AI folder create a models folder.If you do not have an AI folder create one.Go to when your logged into your Google Account.Since you are running Google Colabs I’m going to assume you know you have a Google Drive for file storage. Next steps are to upload this model to your Google drive folder. On the next page you will see a link to download sd-v1-4.ckpt.Go here to download the 1.4 model (current version at the time of writing).You will need to create an account on HugginFace first and then after that you can download the model. If you don’t, please check the appendix for some recommended resources to get that understanding.ĭSD does not come with the stable diffusion model ready to download and you will have to do this process manually. This guide assumes you understand the basics of accessing and running a notebook using Google’s Colab service. Just take it in small steps and you’ll make progress. ****Please note this document also shares a lot of information from the Disco Diffusion Document that I was kindly allowed to use and reuse for this document by Chris Allen ( twitter) Getting Startedĭeforum Stable Diffusion (DSD) (currently version 0.4) is intimidating and inscrutable at first. Some things may get outdated or things might change and we will make our best effort to keep things update and add new things as they come. This document is created from additional resources and should be used as a reference only. Most documentation has been updated to reflect changes in version 0.5 released on October 1st, 2022. It is intended for version 0.4, which was released This quick user guide is intended as a LITE reference for different aspects and items found within the Deforum notebook. Spirit Wolf UniSex T-Shirt $24.44 – $26.70 Select options LAION-Aesthetics will be released with other subsets in the coming days on. LAION-Aesthetics was created with a new CLIP-based model that filtered LAION-5B based on how “beautiful” an image was, building on ratings from the alpha testers of Stable Diffusion. The core dataset was trained on LAION-Aesthetics, a soon to be released subset of LAION 5B. We are delighted that AI media generation is a cooperative field and hope it can continue this way to bring the gift of creativity to all. “The model itself builds upon the work of the team at CompVis and Runway in their widely used latent diffusion model combined with insights from the conditional diffusion models by our lead generative AI developer Katherine Crowson, Dall-E 2 by Open AI, Imagen by Google Brain and many others. Here is a bit more info on whats going on. “ultra detailed portrait Burning Man festival in the Black Rock Desert, steampunk burning man artwork, night time with fractal clouds, volumetric lighting, cinematic portrait” The image above was created with DSD using just the text prompt: Since Stability AI ( blog post) has released this model for free and commercial usages a lot of amazing new notebooks have come out that push this technology further.ĭeforum Stable Diffusion (DSD) as of this writing has additional features such as animation in the form of 2D and 3D, Video Init, and a few other masking options. Otherwise, YouTube converts the unsupported colour spaces to BT.709 by mapping pixel values.Deforum Automatic 1111 Extension is recommended ( link)ĭeforum Stable Diffusion (Design Forum) builds upon Stability AI’s Stable Diffusion Model and add’s a lot of additional functionality not seen in the default notebook by Stability. Uses the specified value of colour primaries/matrix to set and override the unspecified one.Īfter the upload colour space standardisation, YouTube will check if BT.709 or BT.601 matches and passes through the colour space. The upload colour space mixes BT.601 and BT.709 colour primaries and matrix, and either primaries or matrix is unspecified. Uses the colour matrix to override the colour primaries and make them consistent. The upload colour space mixes BT.601 and BT.709 colour primaries and matrix with specified values. The upload colour space has unknown or unspecified colour matrix and primaries.Īssumes BT.709 colour matrix and primaries. The upload colour space has unspecified TRC. In addition, YouTube may take the following actions to interpret the colour space values: When Or, BT.601 NTSC and PAL have functionally similar colour matrices and YouTube unifies them to BT.601 NTSC. For example, BT.601 and BT.709 TRC are identical, and YouTube unifies them to BT.709. YouTube standardises functionally similar colour matrices and primaries before processing the video.
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