gwang-kim/diffusionclip:46349133 | Run with an API on Replicate

Version

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gwang-kim /diffusionclip:46349133

Playground API

Input

image

*file

Input image.

manipulation

string

Choose a manipulation type. Human face manipulation expects aligned image, pre-process with https://replicate.com/cjwbw/face-align-cog for images that are not aligned.

Default: "ImageNet style transfer"

edit_type

string

Choose corresponding edit type available for model chosen.

degree_of_change

number

(minimum: 0, maximum: 1)

Default: 1

n_test_step

integer

(minimum: 5, maximum: 100)

Default: 12

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

npx create-replicate --model=gwang-kim/diffusionclip

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 gwang-kim/diffusionclip using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "gwang-kim/diffusionclip:463491330edabaa793f3407fc1e1ed20a116b7149e8bf2be4a6d5261b33484a5",
  {
    input: {
      edit_type: "ImageNet style transfer - Watercolor art",
      n_test_step: 12,
      manipulation: "ImageNet style transfer",
      degree_of_change: 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=<paste-your-token-here>

Find your API token in your account settings.

Import the client:

import replicate

Run gwang-kim/diffusionclip using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "gwang-kim/diffusionclip:463491330edabaa793f3407fc1e1ed20a116b7149e8bf2be4a6d5261b33484a5",
    input={
        "edit_type": "ImageNet style transfer - Watercolor art",
        "n_test_step": 12,
        "manipulation": "ImageNet style transfer",
        "degree_of_change": 1
    }
)
print(output)

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 gwang-kim/diffusionclip 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": "gwang-kim/diffusionclip:463491330edabaa793f3407fc1e1ed20a116b7149e8bf2be4a6d5261b33484a5",
    "input": {
      "edit_type": "ImageNet style transfer - Watercolor art",
      "n_test_step": 12,
      "manipulation": "ImageNet style transfer",
      "degree_of_change": 1
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

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