![]() ![]() In that case, muCommander may be the app you are looking for. Suppose you are looking for a new file manager with support for many filesystems/archives formats, bookmarks, credentials management, themes, etc. MuCommander also gives you access to a virtual filesystem with support for local volumes, FTP, SFTP, SMB, NFS, HTTP, Amazon S3, Hadoop HDFS, and Bonjour. You can also configure the keyboard shortcuts. It supports multiple tabs and universal bookmarks and includes a credential manager. With muCommander, you can easily copy, move, and batch rename email files and perform checksum calculations from a modern UI. This model card was written by: Robin Rombach and Patrick Esser and is based on the DALL-E Mini model card.MuCommander is a cross-platform file manager with a dual-pane interface. Resources for more information: GitHub Repository, Paper.Ĭite as: = , It is a Latent Diffusion Model that uses a fixed, pretrained text encoder ( CLIP ViT-L/14) as suggested in the Imagen paper. This doesn’t include documentation, source files, or any optional JavaScript dependencies (jQuery and Popper.js). Model Description: This is a model that can be used to generate and modify images based on text prompts. Download ready-to-use compiled code for Bootstrap v4.0.0 to easily drop into your project, which includes: Compiled and minified CSS bundles (see CSS files comparison) Compiled and minified JavaScript plugins. See also the article about the BLOOM Open RAIL license on which our license is based. License: The CreativeML OpenRAIL M license is an Open RAIL M license, adapted from the work that BigScience and the RAIL Initiative are jointly carrying in the area of responsible AI licensing. Model type: Diffusion-based text-to-image generation model If you are looking for the model to use with the D□iffusers library, come here.ĭeveloped by: Robin Rombach, Patrick Esser These weights are intended to be used with the original CompVis Stable Diffusion codebase. ![]() The Stable-Diffusion-v-1-4 checkpoint was initialized with the weights of the Stable-Diffusion-v-1-2Ĭheckpoint and subsequently fine-tuned on 225k steps at resolution 512x512 on "laion-aesthetics v2 5+" and 10% dropping of the text-conditioning to improve classifier-free guidance sampling. ![]() Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. ![]()
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