Prompt Title: stable diffusion

It is possible to run Stable-Diffusion using Google Colab, which allows you to use a GPU provided by Google for free. However, using a GPU provided by Google through Colab may not fully solve the GPU issue when it comes to video generation, as the GPU resources may still be limited and shared among multiple users.

When running Stable-Diffusion on Google Colab, you will need to upload your input images to your Google Drive, and then mount your Google Drive to the Colab environment. This will allow you to access the input images from the Colab notebook.

Here are the basic steps to run Stable-Diffusion on Google Colab:

1. Open a new Colab notebook: Go to https://colab.research.google.com/ and create a new notebook.

2. Connect to a GPU: Click on "Runtime" in the menu bar and select "Change runtime type". Make sure the "Hardware accelerator" is set to "GPU" and then click "Save".

3. Mount your Google Drive: Run the following code in a new cell to mount your Google Drive to the Colab environment:

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from google.colab import drive
drive.mount('/content/drive')

4. Install the required packages: Run the following code in a new cell to install the required packages for Stable-Diffusion:

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!pip install torch torchvision imageio ffmpeg-python

5. Download the Stable-Diffusion code and pre-trained model: Run the following code in a new cell to download the Stable-Diffusion code and pre-trained model:

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!git clone https://github.com/hojonathanho/diffusion.git
!wget https://diffusion-models.s3.us-west-2.amazonaws.com/ddim-s.pk

6. Generate the video: Finally, run the Stable-Diffusion script to generate the video using your input images. Make sure to specify the correct paths to your input images and output video.

It's worth noting that running Stable-Diffusion on Google Colab may still have some limitations, such as limited GPU memory and disk space. However, it can be a good option if you don't have access to a powerful GPU on your local machine.