hongchaodeng / cog-cog-stable-diffusion

{
  "width": "128",
  "height": "128",
  "prompt": "a photo of an astronaut riding a horse on mars",
  "scheduler": "DPMSolverMultistep",
  "num_outputs": 1,
  "guidance_scale": 7.5,
  "num_inference_steps": 8
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";

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

Run hongchaodeng/cog-cog-stable-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "hongchaodeng/cog-cog-stable-diffusion:ad59a4472eb2f99b3d3a7352a1b375625ed5a50ab8c8f4361842a502c8af0f54",
  {
    input: {
      width: "128",
      height: "128",
      prompt: "a photo of an astronaut riding a horse on mars",
      scheduler: "DPMSolverMultistep",
      num_outputs: 1,
      guidance_scale: 7.5,
      num_inference_steps: 8
    }
  }
);

// To access the file URL:
console.log(output[0].url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output[0]);

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

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run hongchaodeng/cog-cog-stable-diffusion using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "hongchaodeng/cog-cog-stable-diffusion:ad59a4472eb2f99b3d3a7352a1b375625ed5a50ab8c8f4361842a502c8af0f54",
    input={
        "width": "128",
        "height": "128",
        "prompt": "a photo of an astronaut riding a horse on mars",
        "scheduler": "DPMSolverMultistep",
        "num_outputs": 1,
        "guidance_scale": 7.5,
        "num_inference_steps": 8
    }
)
print(output)

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

Run hongchaodeng/cog-cog-stable-diffusion 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": "hongchaodeng/cog-cog-stable-diffusion:ad59a4472eb2f99b3d3a7352a1b375625ed5a50ab8c8f4361842a502c8af0f54",
    "input": {
      "width": "128",
      "height": "128",
      "prompt": "a photo of an astronaut riding a horse on mars",
      "scheduler": "DPMSolverMultistep",
      "num_outputs": 1,
      "guidance_scale": 7.5,
      "num_inference_steps": 8
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

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