enhance-replicate/flix1.4

Public

17 runs

Run enhance-replicate/flix1.4 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 video generation, i.e. A formidable Roman warrior in ornate bronze armor strides through the grand Colosseum at dusk, torches flickering along the stone walls as the crowd roars, his crimson cape billowing with each step, portrayed in epic, cinematic grandeur.
negative_prompt	string	Bright tones, overexposed, static, blurred details, subtitles, style, works, paintings, images, static, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards	Negative prompt
height	integer	480	None
width	integer	832	None
num_frames	integer	32	None
num_inference_steps	integer	15	None
guidance_scale	number	5	None
fps	integer	8	None
ken_burns_effect	None	none	Ken Burns effect to apply
target_duration	number	4 Min: 1 Max: 30	Target video duration in seconds
enable_upscaling	boolean	True	Enable GFPGAN upscaling for higher quality output
upscaling_optimization	None	balanced	Upscaling optimization level for speed vs quality trade-off
lora_weight	number	1 Max: 2	LoRA adapter weight (0.0 to 2.0)

{
  "type": "object",
  "title": "Input",
  "required": [
    "prompt"
  ],
  "properties": {
    "fps": {
      "type": "integer",
      "title": "Fps",
      "default": 8,
      "x-order": 7
    },
    "width": {
      "type": "integer",
      "title": "Width",
      "default": 832,
      "x-order": 3
    },
    "height": {
      "type": "integer",
      "title": "Height",
      "default": 480,
      "x-order": 2
    },
    "prompt": {
      "type": "string",
      "title": "Prompt",
      "x-order": 0,
      "description": "Prompt for video generation, i.e. A formidable Roman warrior in ornate bronze armor strides through the grand Colosseum at dusk, torches flickering along the stone walls as the crowd roars, his crimson cape billowing with each step, portrayed in epic, cinematic grandeur."
    },
    "num_frames": {
      "type": "integer",
      "title": "Num Frames",
      "default": 32,
      "x-order": 4
    },
    "lora_weight": {
      "type": "number",
      "title": "Lora Weight",
      "default": 1,
      "maximum": 2,
      "minimum": 0,
      "x-order": 12,
      "description": "LoRA adapter weight (0.0 to 2.0)"
    },
    "guidance_scale": {
      "type": "number",
      "title": "Guidance Scale",
      "default": 5,
      "x-order": 6
    },
    "negative_prompt": {
      "type": "string",
      "title": "Negative Prompt",
      "default": "Bright tones, overexposed, static, blurred details, subtitles, style, works, paintings, images, static, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards",
      "x-order": 1,
      "description": "Negative prompt"
    },
    "target_duration": {
      "type": "number",
      "title": "Target Duration",
      "default": 4,
      "maximum": 30,
      "minimum": 1,
      "x-order": 9,
      "description": "Target video duration in seconds"
    },
    "enable_upscaling": {
      "type": "boolean",
      "title": "Enable Upscaling",
      "default": true,
      "x-order": 10,
      "description": "Enable GFPGAN upscaling for higher quality output"
    },
    "ken_burns_effect": {
      "enum": [
        "none",
        "zoom_pan",
        "zoom_in",
        "zoom_out",
        "pan_left",
        "pan_right",
        "slow_motion",
        "loop",
        "random_effect"
      ],
      "type": "string",
      "title": "ken_burns_effect",
      "description": "Ken Burns effect to apply",
      "default": "none",
      "x-order": 8
    },
    "num_inference_steps": {
      "type": "integer",
      "title": "Num Inference Steps",
      "default": 15,
      "x-order": 5
    },
    "upscaling_optimization": {
      "enum": [
        "fast",
        "balanced",
        "quality"
      ],
      "type": "string",
      "title": "upscaling_optimization",
      "description": "Upscaling optimization level for speed vs quality trade-off",
      "default": "balanced",
      "x-order": 11
    }
  }
}

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"
}