fofr/lcm-video2video:c398af6e – Run with an API on Replicate

Version

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fofr /lcm-video2video:c398af6e

Input

prompt

string

Shift + Return to add a new line

Self-portrait oil painting, a beautiful cyborg with golden hair, 8kSelf-portrait oil painting, a beautiful cyborg with golden hair, 8k

Prompt for video2video

Default: "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k"

video

*file

Video to split into frames

fps

integer

(minimum: 1)

Number of images per second of video, when not exporting all frames

Default: 8

extract_all_frames

boolean

Get every frame of the video. Ignores fps. Slow for large videos.

Default: false

max_width

integer

(minimum: 1)

Maximum width of the video. Maintains aspect ratio.

Default: 512

prompt_strength

number

(minimum: 0, maximum: 1)

1.0 corresponds to full destruction of information in video frame

Default: 0.2

num_inference_steps

integer

(minimum: 1, maximum: 50)

Number of denoising steps per frame. Recommend 1 to 8 steps.

Default: 4

guidance_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance

Default: 8

seed

integer

Random seed. Leave blank to randomize the seed

Run this model in Node.js with one line of code:

npx create-replicate --model=fofr/lcm-video2video

or set up a project from scratch

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run fofr/lcm-video2video using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "fofr/lcm-video2video:c398af6eff3faec4be86fe40544ac01e6ecdb79a6e5fb27a8bf2691051890c2a",
  {
    input: {
      fps: 8,
      prompt: "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k",
      max_width: 512,
      guidance_scale: 8,
      prompt_strength: 0.2,
      extract_all_frames: false,
      num_inference_steps: 4
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run fofr/lcm-video2video using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "fofr/lcm-video2video:c398af6eff3faec4be86fe40544ac01e6ecdb79a6e5fb27a8bf2691051890c2a",
    input={
        "fps": 8,
        "prompt": "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k",
        "max_width": 512,
        "guidance_scale": 8,
        "prompt_strength": 0.2,
        "extract_all_frames": False,
        "num_inference_steps": 4
    }
)
print(output)

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=<paste-your-token-here>

Find your API token in your account settings.

Run fofr/lcm-video2video using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "fofr/lcm-video2video:c398af6eff3faec4be86fe40544ac01e6ecdb79a6e5fb27a8bf2691051890c2a",
    "input": {
      "fps": 8,
      "prompt": "Self-portrait oil painting, a beautiful cyborg with golden hair, 8k",
      "max_width": 512,
      "guidance_scale": 8,
      "prompt_strength": 0.2,
      "extract_all_frames": false,
      "num_inference_steps": 4
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

No output yet! Press "Submit" to start a prediction.