![]() In this post we'll use model version v1-4, but you can also use other versions of the model such as 1.5, 2, and 2.1 with minimal code changes. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users.įirst, you should install diffusers=0.10.2 to run the following code snippets: pip install diffusers=0.10.2 transformers scipy ftfy accelerate You may re-distribute the weights and use the model commercially and/or as a service.We claim no rights on the outputs you generate, you are free to use them and are accountable for their use which should not go against the provisions set in the license, and.You can't use the model to deliberately produce nor share illegal or harmful outputs or content,.We request users to read the license entirely and carefully. The license is designed to mitigate the potential harmful effects of such a powerful machine learning system. Note: the license does not need to be explicitly accepted through the UI anymore. Now, let's get started by generating some images □.īefore using the model, you need to accept the model license in order to download and use the weights. Models are completely new to you, we recommend reading one of the following blog posts: Note: It is highly recommended to have a basic understanding of how diffusion models work. One to customize the image generation pipeline. In this post, we want to show how to use Stable Diffusion with the □ Diffusers library, explain how the model works and finally dive a bit deeper into how diffusers allows ![]() LAION-5B is the largest, freely accessible multi-modal dataset that currently exists. It is trained on 512x512 images from a subset of the LAION-5B database. Stable Diffusion is a text-to-image latent diffusion model created by the researchers and engineers from CompVis, Stability AI and LAION. ![]() Patrickvonplaten Patrick von Platen Stable Diffusion □ ![]()
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