These will act and work just like the checkpoint versions. When you perform a new install of version 2.3.0, you will be offered the option to install the diffusers versions of a number of popular SD models, including Stable Diffusion versions 1.5 and 2.1 (including the 768x768 pixel version of 2.1). A longer term benefit is that in the near future diffusers models will be able to share common sub-models, dramatically reducing disk space when you have multiple fine-tune models derived from the same base. The most immediate benefit of diffusers is that they load from disk very quickly. A new format, introduced by the StabilityAI company in collaboration with HuggingFace, is called diffusers and consists of a directory of individual models. In addition, because checkpoint files are actually a bundle of multiple machine learning sub-models, it is hard to swap different sub-models in and out, or to share common sub-models. Though this format has served the community well, it has a number of disadvantages, including file size, slow loading times, and a variety of non-standard variants that require special-case code to handle. In the original format, known variously as "checkpoint", or "legacy" format, there is a single large weights file ending with. Previous versions of InvokeAI supported the original model file format introduced with Stable Diffusion 1.4. Latest Changes # v2.3.0 (9 February 2023) # Migration to Stable Diffusion diffusers models # WebUI Unified Canvas for Img2Img, inpainting and outpainting.InvokeAI Features # The InvokeAI Web Interface # This method is recommended for those familiar with running Docker containers Other Installation Guides # This method is recommended for experienced users and developers Docker Installation # This method is recommended for 1 st time users Manual Installation # Installation Getting Started Guide # Automated Installer # Linux users can useĮither an Nvidia-based card (with CUDA support) or an AMD card (using the ROCmĭriver). This fork is supported across Linux, Windows and Macintosh. At least 18 GB of free disk space for the machine learning model, Python, and.NVIDIA 10xx series cards such as the 1080ti.Running in half-precision mode and having insufficient VRAM to render 512x512 We do not recommend the following video cards due to issues with their An AMD-based graphics card with 4 GB or more VRAM memory (Linux.An NVIDIA-based graphics card with 4 GB or more VRAM memory.They will help aid diagnose issues faster. Please use the Issues tab to report bugs and make feature requests. Installing InvokeAI with the Pre-Compiled PIP Installer Running InvokeAI on Google Colab using a Jupyter Notebook Support for the XFormers Memory-Efficient Crossattention Package Migration to Stable Diffusion diffusers models
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