login() and enter your Hugging Face Hub access token. Next we install diffusers and dependencies:   Copied pip install -q diffusers accelerate transformers The following sections give more in-detail examples of how to use IF. Specifically: Text-to-Image Generation Image-to-Image Generation Inpainting Reusing model weights Speed optimization Memory optimization Available checkpoints Stage-1 DeepFloyd/IF-I-XL-v1.0 DeepFloyd/IF-I-L-v1.0 DeepFloyd/IF-I-M-v1.0 Stage-2 DeepFloyd/IF-II-L-v1.0 DeepFloyd/IF-II-M-v1.0 Stage-3 stabilityai/stable-diffusion-x4-upscaler Google Colab   Text-to-Image Generation By default diffusers makes use of model cpu offloading to run the whole IF pipeline with as little as 14 GB of VRAM.   Copied from diffusers import DiffusionPipeline