gbergman9 / wes

  • Public
  • 1 run
  • H100
  • Fine-tune

Input

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

npx create-replicate --model=gbergman9/wes
or set up a project from scratch
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 gbergman9/wes using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "gbergman9/wes:edabaff1306e44f3ca2c70b73c6152cba65566d47dba928740252ee645ce5e02",
  {
    input: {
      crf: 19,
      steps: 50,
      width: 640,
      height: 360,
      prompt: "",
      lora_url: "",
      scheduler: "DPMSolverMultistepScheduler",
      flow_shift: 9,
      frame_rate: 16,
      num_frames: 33,
      enhance_end: 1,
      enhance_start: 0,
      force_offload: true,
      lora_strength: 1,
      enhance_double: true,
      enhance_single: true,
      enhance_weight: 0.3,
      guidance_scale: 6,
      denoise_strength: 1
    }
  }
);

// 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.

Output

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

Run time and cost

This model runs on Nvidia H100 GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.