thefluxtrain/oye-cartoon:a4862b81 – Run with an API on Replicate

Version

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thefluxtrain /oye-cartoon:a4862b81

Input

prompt

string

Shift + Return to add a new line

A girl cartoon character in a white background. She is looking right, and running.A girl cartoon character in a white background. She is looking right, and running.

Input prompt.

Default: "A girl cartoon character in a white background. She is looking right, and running."

image

*file

Input image

num_inference_steps

integer

(minimum: 1, maximum: 150)

Number of denoising steps

Default: 30

model

string

Control model to use.

Default: "oye-cartoon-v2"

Including guidance_scale and 14 more...

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

npx create-replicate --model=thefluxtrain/oye-cartoon

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";

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

Run thefluxtrain/oye-cartoon using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "thefluxtrain/oye-cartoon:a4862b811bb3af0baf99cff192e2649bda525b441696d02fb80f40ce52290652",
  {
    input: {
      lora: "saquiboye/oye-cartoon",
      model: "oye-cartoon-v2",
      prompt: "A girl cartoon character in a white background. She is looking right, and running.",
      strength: 0.6,
      predictive: 0,
      weight_name: "pytorch_lora_weights.safetensors",
      guidance_scale: 7.5,
      image_strength: 1,
      position_delta: -16,
      num_inference_steps: 30
    }
  }
);

// 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 thefluxtrain/oye-cartoon using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "thefluxtrain/oye-cartoon:a4862b811bb3af0baf99cff192e2649bda525b441696d02fb80f40ce52290652",
    input={
        "lora": "saquiboye/oye-cartoon",
        "model": "oye-cartoon-v2",
        "prompt": "A girl cartoon character in a white background. She is looking right, and running.",
        "strength": 0.6,
        "predictive": 0,
        "weight_name": "pytorch_lora_weights.safetensors",
        "guidance_scale": 7.5,
        "image_strength": 1,
        "position_delta": -16,
        "num_inference_steps": 30
    }
)
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 thefluxtrain/oye-cartoon 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": "a4862b811bb3af0baf99cff192e2649bda525b441696d02fb80f40ce52290652",
    "input": {
      "lora": "saquiboye/oye-cartoon",
      "model": "oye-cartoon-v2",
      "prompt": "A girl cartoon character in a white background. She is looking right, and running.",
      "strength": 0.6,
      "predictive": 0,
      "weight_name": "pytorch_lora_weights.safetensors",
      "guidance_scale": 7.5,
      "image_strength": 1,
      "position_delta": -16,
      "num_inference_steps": 30
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

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