Prediction

Model

daanelson/stable-diffusion-speed-lab:05aca4ae

dk6eqsktbnajzcbdwwy4vydqra

Status

Succeeded

Source

Web

Hardware

–

Total duration

1.9s

Created

almost 3 years ago by daanelson

Webhook

–

Input

prompt: 👨‍🚀🦅, digital Art, Greg rutkowski, Trending artstation,cinematographic
num_outputs: 1
num_inference_steps: 50
guidance_scale: 7.5
scheduler: DPMSolverMultistep

{
  "guidance_scale": 7.5,
  "num_inference_steps": 50,
  "num_outputs": 1,
  "prompt": "👨‍🚀🦅, digital Art, Greg rutkowski, Trending artstation,cinematographic",
  "scheduler": "DPMSolverMultistep"
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_PcU**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

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

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

const output = await replicate.run(
  "daanelson/stable-diffusion-speed-lab:05aca4aea54103353540845627a4ac45412195df3b099f9f4d932f58a5ccb820",
  {
    input: {
      guidance_scale: 7.5,
      num_inference_steps: 50,
      num_outputs: 1,
      prompt: "👨‍🚀🦅, digital Art, Greg rutkowski, Trending artstation,cinematographic",
      scheduler: "DPMSolverMultistep"
    }
  }
);

// 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

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_PcU**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

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

output = replicate.run(
    "daanelson/stable-diffusion-speed-lab:05aca4aea54103353540845627a4ac45412195df3b099f9f4d932f58a5ccb820",
    input={
        "guidance_scale": 7.5,
        "num_inference_steps": 50,
        "num_outputs": 1,
        "prompt": "👨‍🚀🦅, digital Art, Greg rutkowski, Trending artstation,cinematographic",
        "scheduler": "DPMSolverMultistep"
    }
)

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

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output[0].read())

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=r8_PcU**********************************

This is your API token. Keep it to yourself.

Run daanelson/stable-diffusion-speed-lab 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": "daanelson/stable-diffusion-speed-lab:05aca4aea54103353540845627a4ac45412195df3b099f9f4d932f58a5ccb820",
    "input": {
      "guidance_scale": 7.5,
      "num_inference_steps": 50,
      "num_outputs": 1,
      "prompt": "👨‍🚀🦅, digital Art, Greg rutkowski, Trending artstation,cinematographic",
      "scheduler": "DPMSolverMultistep"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

1.9 second

Tweak it Report