replicategithubwc/stable-video-diffusion

replicategithubwc / stable-video-diffusion

Public
11 runs

Run replicategithubwc/stable-video-diffusion with an API

Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.

Input schema

The fields you can use to run this model with an API. If you don't give a value for a field its default value will be used.

Field	Type	Default value	Description
prompt	string	astronaut riding a horse on mars, beautiful, 8k, perfect, award winning, national geographic	Input prompt
negative_prompt	string	very blue, dust, noisy, washed out, ugly, distorted, broken	Specify things to not see in the output
width	integer	1024	Width of output image
height	integer	576	Height of output image
num_frames	integer	24	Number of frames for the output video
fps	integer	24	fps for the output video
num_inference_steps	integer	50 Min: 1 Max: 500	Number of denoising steps
guidance_scale	number	12.5 Min: 1 Max: 20	Scale for classifier-free guidance
scheduler	string (enum)	K_EULER_ANCESTRAL Options: DDIM, K_EULER, DPMSolverMultistep, K_EULER_ANCESTRAL, PNDM, KLMS, DEISMultistepScheduler, DPM++_2M_Karras	Choose a scheduler.
seed	integer		Random seed. Leave blank to randomize the seed

{
  "type": "object",
  "title": "Input",
  "properties": {
    "fps": {
      "type": "integer",
      "title": "Fps",
      "default": 24,
      "x-order": 5,
      "description": "fps for the output video"
    },
    "seed": {
      "type": "integer",
      "title": "Seed",
      "x-order": 9,
      "description": "Random seed. Leave blank to randomize the seed"
    },
    "width": {
      "type": "integer",
      "title": "Width",
      "default": 1024,
      "x-order": 2,
      "description": "Width of output image"
    },
    "height": {
      "type": "integer",
      "title": "Height",
      "default": 576,
      "x-order": 3,
      "description": "Height of output image"
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "default": "astronaut riding a horse on mars, beautiful, 8k, perfect, award winning, national geographic",
      "x-order": 0,
      "description": "Input prompt"
    },
    "scheduler": {
      "enum": [
        "DDIM",
        "K_EULER",
        "DPMSolverMultistep",
        "K_EULER_ANCESTRAL",
        "PNDM",
        "KLMS",
        "DEISMultistepScheduler",
        "DPM++_2M_Karras"
      ],
      "type": "string",
      "title": "scheduler",
      "description": "Choose a scheduler.",
      "default": "K_EULER_ANCESTRAL",
      "x-order": 8
    },
    "num_frames": {
      "type": "integer",
      "title": "Num Frames",
      "default": 24,
      "x-order": 4,
      "description": "Number of frames for the output video"
    },
    "guidance_scale": {
      "type": "number",
      "title": "Guidance Scale",
      "default": 12.5,
      "maximum": 20,
      "minimum": 1,
      "x-order": 7,
      "description": "Scale for classifier-free guidance"
    },
    "negative_prompt": {
      "type": "string",
      "title": "Negative Prompt",
      "default": "very blue, dust, noisy, washed out, ugly, distorted, broken",
      "x-order": 1,
      "description": "Specify things to not see in the output"
    },
    "num_inference_steps": {
      "type": "integer",
      "title": "Num Inference Steps",
      "default": 50,
      "maximum": 500,
      "minimum": 1,
      "x-order": 6,
      "description": "Number of denoising steps"
    }
  }
}

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema

{
  "type": "string",
  "title": "Output",
  "format": "uri"
}