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@ -19,38 +19,26 @@ Latent blending allows you to generate smooth video transitions between two prom
```commandline ```commandline
pip install -r requirements.txt pip install -r requirements.txt
``` ```
#### Models #### Download Models from Huggingface
[Download the Stable Diffusion 2.0 Standard Model](https://huggingface.co/stabilityai/stable-diffusion-2) [Download the Stable Diffusion 2.0 Standard Model](https://huggingface.co/stabilityai/stable-diffusion-2)
[Download the Stable Diffusion 2.0 Inpainting Model (optional)](https://huggingface.co/stabilityai/stable-diffusion-2-inpainting) [Download the Stable Diffusion 2.0 Inpainting Model (optional)](https://huggingface.co/stabilityai/stable-diffusion-2-inpainting)
#### xformers efficient attention [(copied from stability)](https://github.com/Stability-AI/stablediffusion) #### Install [Xformers](https://github.com/facebookresearch/xformers)
For more efficiency and speed on GPUs, With xformers, stable diffusion 2 will run much faster. The recommended way of installation is via the supplied binaries (Linux).
we highly recommended installing the [xformers](https://github.com/facebookresearch/xformers)
library.
Tested on A100 with CUDA 11.4.
Installation needs a somewhat recent version of nvcc and gcc/g++, obtain those, e.g., via
```commandline
export CUDA_HOME=/usr/local/cuda-11.4
conda install -c nvidia/label/cuda-11.4.0 cuda-nvcc
conda install -c conda-forge gcc
conda install -c conda-forge gxx_linux-64=9.5.0
```
Then, run the following (compiling takes up to 30 min).
```commandline ```commandline
cd .. conda install xformers -c xformers/label/dev
git clone https://github.com/facebookresearch/xformers.git ```
cd xformers
git submodule update --init --recursive Alternatively, you can build it from source:
pip install -r requirements.txt ```commandline
pip install -e . # (Optional) Makes the build much faster
cd ../stable-diffusion pip install ninja
# Set TORCH_CUDA_ARCH_LIST if running and building on different GPU types
pip install -v -U git+https://github.com/facebookresearch/xformers.git@main#egg=xformers
# (this can take dozens of minutes)
``` ```
Upon successful installation, the code will automatically default to [memory efficient attention](https://github.com/facebookresearch/xformers)
for the self- and cross-attention layers in the U-Net and autoencoder.
# How does it work # How does it work
![](animation.gif) ![](animation.gif)