Other Use Cases
Model Demo

Model Demo

In this tutorial, we will run Stable Diffusion model to generate an image from text. Specifically, we want the model to generate a photo of an astronaut riding a horse on mars. The image is stored on EverlyAI file storage and it can be downloaded from web UI (opens in a new tab).

Step 1 Implement Code

The final folder structure is shown below.

    • everlyai_entrypoint.sh
    • stable_diffusion.py
    • code.zip
  • everlyai_entrypoint.sh is the entrypoint of the server. It contains code to install dependencies and start the server.

    python3 -m pip install diffusers transformers accelerate scipy safetensors
    python3 stable_diffusion.py

    stable_diffusion.py contains the entire image generation code, adapted from Huggingface model card (opens in a new tab).

    Note that the image is saved inside directory, /everlyai/fs. This will automatically store the file inside EverlyAI's persistent file storage.

    import torch
    from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler
    model_id = "stabilityai/stable-diffusion-2"
    # Use the Euler scheduler here instead
    scheduler = EulerDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler")
    pipe = StableDiffusionPipeline.from_pretrained(model_id, scheduler=scheduler, torch_dtype=torch.float16)
    pipe = pipe.to("cuda")
    prompt = "a photo of an astronaut riding a horse on mars"
    image = pipe(prompt).images[0]

    Inside the project directory, my_awesome_project, run the following command to generate the code.zip file. And now we are ready to start the project on EverlyAI.

    zip code.zip everlyai_entrypoint.sh stable_diffusion.py

    Step 2 Start Project

    Go to EverlyAI project (opens in a new tab) page. Start the project with the following configuration.

    Step 3 Verify Result

    Wait until the job completes. We can now navigate to file storage (opens in a new tab) page. You should be able to see and download the image from there.