anhappdev/test:533e970b | Run with an API on Replicate

Version

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anhappdev /test:533e970b

Input

prompt

string

Shift + Return to add a new line

a photo of an astronaut riding a horse on marsa photo of an astronaut riding a horse on mars

Input prompt

Default: "a photo of an astronaut riding a horse on mars"

negative_prompt

string

Shift + Return to add a new line

Specify things to not see in the output

image

*file

Initial image to generate variations of.

mask_image

*file

Black and white image to use as mask for inpainting over the image provided. White pixels are inpainted and black pixels are preserved

preprocessing

string

Max image size is 512x512. Bigger image will be resized.

Default: "pad"

num_outputs

integer

(minimum: 1, maximum: 4)

Number of images to output. Higher number of outputs may cause OOM.

Default: 1

num_inference_steps

integer

(minimum: 1, maximum: 50)

Number of denoising steps

Default: 25

guidance_scale

number

(minimum: 1, maximum: 20)

Scale for classifier-free guidance

Default: 7.5

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=anhappdev/test

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";
import fs from "node:fs";

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

Run anhappdev/test using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "anhappdev/test:533e970bd09e0fa344168d1c3229ddb89fedbd37e102d8cb935f10ce95137c4a",
  {
    input: {
      prompt: "a photo of an astronaut riding a horse on mars",
      num_outputs: 1,
      preprocessing: "pad",
      guidance_scale: 7.5,
      num_inference_steps: 25
    }
  }
);

// 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=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run anhappdev/test using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "anhappdev/test:533e970bd09e0fa344168d1c3229ddb89fedbd37e102d8cb935f10ce95137c4a",
    input={
        "prompt": "a photo of an astronaut riding a horse on mars",
        "num_outputs": 1,
        "preprocessing": "pad",
        "guidance_scale": 7.5,
        "num_inference_steps": 25
    }
)

# 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=<paste-your-token-here>

Find your API token in your account settings.

Run anhappdev/test 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": "anhappdev/test:533e970bd09e0fa344168d1c3229ddb89fedbd37e102d8cb935f10ce95137c4a",
    "input": {
      "prompt": "a photo of an astronaut riding a horse on mars",
      "num_outputs": 1,
      "preprocessing": "pad",
      "guidance_scale": 7.5,
      "num_inference_steps": 25
    }
  }' \
  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.