Prediction

Model

prunaai/stable-diffusion-cheetah:bce45013

x844dqthq9rj40cnwa98cdkd64

Status

Succeeded

Source

Web

Hardware

A100 (80GB)

Total duration

0.6s

Created

9 months ago

Webhook

–

Input

prompt: a red apple on a table
go_fast_af: false
num_images: 1
num_inference_steps: 50
guidance_scale: 7.5
seed: -1
image_height: 512
image_width: 512

{
  "go_fast_af": false,
  "guidance_scale": 7.5,
  "image_height": 512,
  "image_width": 512,
  "num_images": 1,
  "num_inference_steps": 50,
  "prompt": "a red apple on a table",
  "seed": -1
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_J2E**********************************

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

const output = await replicate.run(
  "prunaai/stable-diffusion-cheetah:bce45013ec9e0034b87dbb81bca9458b57922c0dbdae6901603780ba6ca15fb6",
  {
    input: {
      go_fast_af: false,
      guidance_scale: 7.5,
      image_height: 512,
      image_width: 512,
      num_images: 1,
      num_inference_steps: 50,
      prompt: "a red apple on a table",
      seed: -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.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_J2E**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

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

output = replicate.run(
    "prunaai/stable-diffusion-cheetah:bce45013ec9e0034b87dbb81bca9458b57922c0dbdae6901603780ba6ca15fb6",
    input={
        "go_fast_af": False,
        "guidance_scale": 7.5,
        "image_height": 512,
        "image_width": 512,
        "num_images": 1,
        "num_inference_steps": 50,
        "prompt": "a red apple on a table",
        "seed": -1
    }
)

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

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.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_J2E**********************************

This is your API token. Keep it to yourself.

Run prunaai/stable-diffusion-cheetah 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": "prunaai/stable-diffusion-cheetah:bce45013ec9e0034b87dbb81bca9458b57922c0dbdae6901603780ba6ca15fb6",
    "input": {
      "go_fast_af": false,
      "guidance_scale": 7.5,
      "image_height": 512,
      "image_width": 512,
      "num_images": 1,
      "num_inference_steps": 50,
      "prompt": "a red apple on a table",
      "seed": -1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

Generated in

0.6 seconds

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