Deploy SDXL Lightning

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Example usage

The model accepts a single input, prompt, and returns a base64 string of the image as the key result. This implementation uses the 4-step UNet checkpoint to balance speed and quality. You can deploy your own version with either 2 steps for even faster results or 8 steps for even higher quality. 
import base64
import requests
import os

# Replace the empty string with your model id below
model_id = ""
baseten_api_key = os.environ["BASETEN_API_KEY"]
BASE64_PREAMBLE = "data:image/png;base64,"

data = {
    "prompt": "a picture of a rhino wearing a suit",
}

# Call model endpoint
res = requests.post(
    f"https://model-{model_id}.api.baseten.co/production/predict",
    headers={"Authorization": f"Api-Key {baseten_api_key}"},
    json=data
)

# Get output image
res = res.json()
img_b64 = res.get("result")
img = base64.b64decode(img_b64)

# Save the base64 string to a PNG
img_file = open("sdxl-output-1.png", "wb")
img_file.write(img)
img_file.close()
os.system("open sdxl-output-1.png")
JSON Output 
{
  "result": "iVBORw0KGgoAAAANSUhEUgAABAAAAAQACAIAAA..."
}