camenduru/attribute-control – Run with an API on Replicate

camenduru / attribute-control

Continuous, Subject-Specific Attribute Control in T2I Models by Identifying Semantic Directions

Cold

Public
105 runs
L40S
GitHub
Paper
License

Run with an API

Playground API Examples README Versions

Input

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

npx create-replicate --model=camenduru/attribute-control

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 camenduru/attribute-control using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "camenduru/attribute-control:2f75fb302a6ff587cad3d57fa113ea690c189ead618757cce9772b051d609062",
  {
    input: {
      seed: 0,
      prompt: "a photo of a beautiful man",
      num_images: 6,
      delay_relative: 0.2,
      guidance_scale: 7.5,
      pattern_target: "man",
      prompt_negative: "",
      pretrained_deltas: "person_age"
    }
  }
);
console.log(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 camenduru/attribute-control using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "camenduru/attribute-control:2f75fb302a6ff587cad3d57fa113ea690c189ead618757cce9772b051d609062",
    input={
        "seed": 0,
        "prompt": "a photo of a beautiful man",
        "num_images": 6,
        "delay_relative": 0.2,
        "guidance_scale": 7.5,
        "pattern_target": "man",
        "prompt_negative": "",
        "pretrained_deltas": "person_age"
    }
)
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 camenduru/attribute-control 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": "2f75fb302a6ff587cad3d57fa113ea690c189ead618757cce9772b051d609062",
    "input": {
      "seed": 0,
      "prompt": "a photo of a beautiful man",
      "num_images": 6,
      "delay_relative": 0.2,
      "guidance_scale": 7.5,
      "pattern_target": "man",
      "prompt_negative": "",
      "pretrained_deltas": "person_age"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Install Cog

brew install cog

If you don’t have Homebrew, there are other installation options available.

Pull and run camenduru/attribute-control using Cog (this will download the full model and run it in your local environment):

cog predict r8.im/camenduru/attribute-control@sha256:2f75fb302a6ff587cad3d57fa113ea690c189ead618757cce9772b051d609062 \
  -i 'seed=0' \
  -i 'prompt="a photo of a beautiful man"' \
  -i 'num_images=6' \
  -i 'delay_relative=0.2' \
  -i 'guidance_scale=7.5' \
  -i 'pattern_target="man"' \
  -i 'prompt_negative=""' \
  -i 'pretrained_deltas="person_age"'

To learn more, take a look at the Cog documentation.

Pull and run camenduru/attribute-control using Docker (this will download the full model and run it in your local environment):

docker run -d -p 5000:5000 r8.im/camenduru/attribute-control@sha256:2f75fb302a6ff587cad3d57fa113ea690c189ead618757cce9772b051d609062
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "seed": 0,
      "prompt": "a photo of a beautiful man",
      "num_images": 6,
      "delay_relative": 0.2,
      "guidance_scale": 7.5,
      "pattern_target": "man",
      "prompt_negative": "",
      "pretrained_deltas": "person_age"
    }
  }' \
  http://localhost:5000/predictions

Output

{
  "completed_at": "2024-03-31T02:37:52.932291Z",
  "created_at": "2024-03-31T02:34:34.633299Z",
  "data_removed": false,
  "error": null,
  "id": "c2rnh5tbxvicn7vduxslvjkyju",
  "input": {
    "seed": 0,
    "prompt": "a photo of a beautiful man",
    "num_images": 6,
    "delay_relative": 0.2,
    "guidance_scale": 7.5,
    "pattern_target": "man",
    "prompt_negative": "",
    "pretrained_deltas": "person_age"
  },
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  "metrics": {
    "predict_time": 69.882401,
    "total_time": 198.298992
  },
  "output": [
    "https://replicate.delivery/pbxt/59oh8f5XZtVgGap1RYY6vuEG1rrPKZ1LMsU7V0rtgWze5nlSA/1.png",
    "https://replicate.delivery/pbxt/60VtB9eJxrWcUCuAm7MB14PFbnafwqcunZin6BdtXevenfsUC/2.png",
    "https://replicate.delivery/pbxt/MtNt8sE4fGy8KavYe8qrFnUK1yTlEnZ8Qx1lHe5RJ7jenfsUC/3.png",
    "https://replicate.delivery/pbxt/xcjBxEPqYvbZF5BFYhzCuZ8H78FfS41Y6tTZb33ZG1zf5nlSA/4.png",
    "https://replicate.delivery/pbxt/KJsU9YNSpHabJdQ3BOueDNLYJT4YEqj0CmO8T6aKfOWA6nlSA/5.png",
    "https://replicate.delivery/pbxt/Ijs75WxblE4TMNgeN2rC1NlTLWSbyHZlKxh8fuurXRBA6nlSA/6.png"
  ],
  "started_at": "2024-03-31T02:36:43.049890Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/c2rnh5tbxvicn7vduxslvjkyju",
    "cancel": "https://api.replicate.com/v1/predictions/c2rnh5tbxvicn7vduxslvjkyju/cancel"
  },
  "version": "2d3d06f5437eead1e38fa245b490c785b2d5b15698a7434d6ec87deba7dd3330"
}

Generated in

69.9 seconds

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This example was created by a different version, camenduru/attribute-control:2d3d06f5.

Examples

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Run time and cost

This model runs on Nvidia L40S GPU hardware. We don't yet have enough runs of this model to provide performance information.

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