anotherjesse/temporalnet-v2

anotherjesse / temporalnet-v2

draft version of temporalnet v2

Public
77 runs

Run anotherjesse/temporalnet-v2 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		Prompt for the model
input_video	string		Input video
strength	number	0.7	How heavily stylization affects the image
controlnet_scale	number	1	Controlnet conditioning scale
canny_scale	number	1	Canny conditioning scale
width	integer	512	width
height	integer	512	height
batch_size	integer	4	Batch size (more = faster but more memory)
num_inference_steps	integer	20	Steps to run denoising
guidance_scale	number	7.5 Min: 0.1 Max: 30	Scale for classifier-free guidance
seed	integer		Seed

{
  "type": "object",
  "title": "Input",
  "required": [
    "prompt",
    "input_video"
  ],
  "properties": {
    "seed": {
      "type": "integer",
      "title": "Seed",
      "x-order": 10,
      "description": "Seed"
    },
    "width": {
      "type": "integer",
      "title": "Width",
      "default": 512,
      "x-order": 5,
      "description": "width"
    },
    "height": {
      "type": "integer",
      "title": "Height",
      "default": 512,
      "x-order": 6,
      "description": "height"
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "x-order": 0,
      "description": "Prompt for the model"
    },
    "strength": {
      "type": "number",
      "title": "Strength",
      "default": 0.7,
      "x-order": 2,
      "description": "How heavily stylization affects the image"
    },
    "batch_size": {
      "type": "integer",
      "title": "Batch Size",
      "default": 4,
      "x-order": 7,
      "description": "Batch size (more = faster but more memory)"
    },
    "canny_scale": {
      "type": "number",
      "title": "Canny Scale",
      "default": 1,
      "x-order": 4,
      "description": "Canny conditioning scale"
    },
    "input_video": {
      "type": "string",
      "title": "Input Video",
      "format": "uri",
      "x-order": 1,
      "description": "Input video"
    },
    "guidance_scale": {
      "type": "number",
      "title": "Guidance Scale",
      "default": 7.5,
      "maximum": 30,
      "minimum": 0.1,
      "x-order": 9,
      "description": "Scale for classifier-free guidance"
    },
    "controlnet_scale": {
      "type": "number",
      "title": "Controlnet Scale",
      "default": 1,
      "x-order": 3,
      "description": "Controlnet conditioning scale"
    },
    "num_inference_steps": {
      "type": "integer",
      "title": "Num Inference Steps",
      "default": 20,
      "x-order": 8,
      "description": "Steps to run denoising"
    }
  }
}

Output schema

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

Schema

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