KServe Compatible Demo Model Server

This is a demo model server that can run inside Openshift AI as a KServe model server. It exposes a way to perform inference with a Stable Diffusion compatible model in the backend.

Parameters

The server expects a JSON-encoded payload to start inference:

 // example payload:
 {
   "instances": [
     {
       "prompt": "photo of the beach",
       "negative_prompt": "ugly, deformed, bad anatomy",
       "num_inference_steps": 20,
       "scheduler": "DPM++ SDE",
     }
   ]
 }

Known Parameters:

• "prompt": the stable diffusion positive prompt
• "negative_prompt": put here all negative embeddings
• "num_inference_steps": number of generation steps to run during inference
• "width" and "height": size of the generated image
• "guidance_scale": the guidance scale value to feed to the neural network
• "seed": if specified, use this value as the generation seed.
• "scheduler": Noise Scheduler to use during generation (DPM++ 2M, DPM++ SDE, Euler and Euler a, Heun and LMS)