zelenioncode/ttt:9bafdf31 – Run with an API on Replicate

Version

You're looking at a specific version of this model. Jump to the model overview.

zelenioncode /ttt:9bafdf31

Playground API

Input

input

*string

Shift + Return to add a new line

Need to enter a json, for more information check the documentation

gender

string

Need to choice a gender for the prediction

Default: "woman"

age

string

Need to choice a age for the prediction

Default: "12 et 18 ans"

ethnicity

string

Need to choice a ethnicity for the prediction

Default: "Je ne sais pas"

eye_color

string

Need to choice a eye color for the prediction

Default: "Je ne sais pas"

safetensors

string

Shift + Return to add a new line

https://huggingface.co/SG161222/RealVisXL_V4.0/resolve/main/RealVisXL_V4.0.safetensors?download=truehttps://huggingface.co/SG161222/RealVisXL_V4.0/resolve/main/RealVisXL_V4.0.safetensors?download=true

WARNING ! If you make a training with this model, you don't need to do something with this input. Need to choice a safetensors for the prediction.

Default: "https://huggingface.co/SG161222/RealVisXL_V4.0/resolve/main/RealVisXL_V4.0.safetensors?download=true"

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

npx create-replicate --model=zelenioncode/ttt

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

const output = await replicate.run(
  "zelenioncode/ttt:9bafdf311703fb8299b08f0d66a0c1434ed0d00df28a64ffea7309cc340ad7d9",
  {
    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"
    }
  }
);
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 zelenioncode/ttt using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "zelenioncode/ttt:9bafdf311703fb8299b08f0d66a0c1434ed0d00df28a64ffea7309cc340ad7d9",
    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/ttt 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": "9bafdf311703fb8299b08f0d66a0c1434ed0d00df28a64ffea7309cc340ad7d9",
    "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.

Install Cog

brew install cog

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

Pull and run zelenioncode/ttt using Cog (this will download the full model and run it in your local environment):

cog predict r8.im/zelenioncode/ttt@sha256:9bafdf311703fb8299b08f0d66a0c1434ed0d00df28a64ffea7309cc340ad7d9 \
  -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.

Pull and run zelenioncode/ttt using Docker (this will download the full model and run it in your local environment):

docker run -d -p 5000:5000 --gpus=all r8.im/zelenioncode/ttt@sha256:9bafdf311703fb8299b08f0d66a0c1434ed0d00df28a64ffea7309cc340ad7d9
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

Output

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