zelenioncode/4f99405d-ec6f-4ba5-a4cc-3bd2d21d11b0

zelenioncode / 4f99405d-ec6f-4ba5-a4cc-3bd2d21d11b0

Model for the AiPicture

Cold

Public
1 run
L40S

Iterate in playground

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=zelenioncode/4f99405d-ec6f-4ba5-a4cc-3bd2d21d11b0

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 zelenioncode/4f99405d-ec6f-4ba5-a4cc-3bd2d21d11b0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "zelenioncode/4f99405d-ec6f-4ba5-a4cc-3bd2d21d11b0:713503a7d31b2154889e4c1f1a192a185e20d7da8dd088ed55110161912d61d3",
  {
    input: {
      age: "12 et 18 ans",
      gender: "woman",
      ethnicity: "Je ne sais pas",
      eye_color: "Je ne sais pas",
      safetensors: "https://huggingface.co/SG161222/RealVisXL_V4.0/resolve/main/RealVisXL_V4.0.safetensors?download=true"
    }
  }
);

// 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 zelenioncode/4f99405d-ec6f-4ba5-a4cc-3bd2d21d11b0 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "zelenioncode/4f99405d-ec6f-4ba5-a4cc-3bd2d21d11b0:713503a7d31b2154889e4c1f1a192a185e20d7da8dd088ed55110161912d61d3",
    input={
        "age": "12 et 18 ans",
        "gender": "woman",
        "ethnicity": "Je ne sais pas",
        "eye_color": "Je ne sais pas",
        "safetensors": "https://huggingface.co/SG161222/RealVisXL_V4.0/resolve/main/RealVisXL_V4.0.safetensors?download=true"
    }
)
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 zelenioncode/4f99405d-ec6f-4ba5-a4cc-3bd2d21d11b0 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": "zelenioncode/4f99405d-ec6f-4ba5-a4cc-3bd2d21d11b0:713503a7d31b2154889e4c1f1a192a185e20d7da8dd088ed55110161912d61d3",
    "input": {
      "age": "12 et 18 ans",
      "gender": "woman",
      "ethnicity": "Je ne sais pas",
      "eye_color": "Je ne sais pas",
      "safetensors": "https://huggingface.co/SG161222/RealVisXL_V4.0/resolve/main/RealVisXL_V4.0.safetensors?download=true"
    }
  }' \
  https://api.replicate.com/v1/predictions

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

You can run this model locally using Cog. First, install Cog:

brew install cog

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

Run this to download the model and run it in your local environment:

cog predict r8.im/zelenioncode/4f99405d-ec6f-4ba5-a4cc-3bd2d21d11b0@sha256:713503a7d31b2154889e4c1f1a192a185e20d7da8dd088ed55110161912d61d3 \
  -i 'age="12 et 18 ans"' \
  -i 'gender="woman"' \
  -i 'ethnicity="Je ne sais pas"' \
  -i 'eye_color="Je ne sais pas"' \
  -i 'safetensors="https://huggingface.co/SG161222/RealVisXL_V4.0/resolve/main/RealVisXL_V4.0.safetensors?download=true"'

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

Run this to download the model and run it in your local environment:

docker run -d -p 5000:5000 --gpus=all r8.im/zelenioncode/4f99405d-ec6f-4ba5-a4cc-3bd2d21d11b0@sha256:713503a7d31b2154889e4c1f1a192a185e20d7da8dd088ed55110161912d61d3
curl -s -X POST \
  -H "Content-Type: application/json" \
  -d $'{
    "input": {
      "age": "12 et 18 ans",
      "gender": "woman",
      "ethnicity": "Je ne sais pas",
      "eye_color": "Je ne sais pas",
      "safetensors": "https://huggingface.co/SG161222/RealVisXL_V4.0/resolve/main/RealVisXL_V4.0.safetensors?download=true"
    }
  }' \
  http://localhost:5000/predictions

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

Output

No output yet! Press "Submit" to start a prediction.

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.

Readme

This model doesn't have a readme.