andreasjansson/train-dynamic-system:1415865f | Run with an API on Replicate

Version

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andreasjansson /train-dynamic-system:1415865f

Playground API

Input

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

npx create-replicate --model=andreasjansson/train-dynamic-system

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 andreasjansson/train-dynamic-system using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "andreasjansson/train-dynamic-system:1415865fee9c0cec7e62b699e464c63af110627b1e699cf769b6454ba96a016d",
  {
    input: {
      width: 128,
      height: 128,
      loss_cycles: 4,
      yield_every: 250,
      cycle_length: 12,
      total_cycles: 6,
      learning_rate: 0.005,
      max_variables: 100,
      training_steps: 1000,
      return_animation: 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 andreasjansson/train-dynamic-system using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "andreasjansson/train-dynamic-system:1415865fee9c0cec7e62b699e464c63af110627b1e699cf769b6454ba96a016d",
    input={
        "width": 128,
        "height": 128,
        "loss_cycles": 4,
        "yield_every": 250,
        "cycle_length": 12,
        "total_cycles": 6,
        "learning_rate": 0.005,
        "max_variables": 100,
        "training_steps": 1000,
        "return_animation": True
    }
)

# The andreasjansson/train-dynamic-system model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/andreasjansson/train-dynamic-system/api#output-schema
    print(item)

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 andreasjansson/train-dynamic-system 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": "andreasjansson/train-dynamic-system:1415865fee9c0cec7e62b699e464c63af110627b1e699cf769b6454ba96a016d",
    "input": {
      "width": 128,
      "height": 128,
      "loss_cycles": 4,
      "yield_every": 250,
      "cycle_length": 12,
      "total_cycles": 6,
      "learning_rate": 0.005,
      "max_variables": 100,
      "training_steps": 1000,
      "return_animation": true
    }
  }' \
  https://api.replicate.com/v1/predictions

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

Output

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