With Client SDKs you can call custom or public AI model with just one line of code!

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Prerequisite

  • Select a model from Model Yard
  • Create an API Key

You can use three ways to call a model on Each

Client SDK

Run with just a single line. each.run()

Console

Run from UI. Easy and effective for testing!

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Client SDK

With Client SDK you need to initialize our SDK in your langauage and then you may able to use custom methods and calls to Each backend servers.

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Initialize SDK

// Please make sure that you run 'npm install @eachlabs/aiflow@latest'
import Each from '@eachlabs/aiflow';

const each = new Each({
    auth: process.env.EACH_API_KEY || 'YOUR_API_KEY'
});

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Run Inference

// Please make sure that you run 'npm install @eachlabs/aiflow'
import Each from '@eachlabs/aiflow';
const each = new Each({
    auth: process.env.EACH_API_KEY || 'YOUR_API_KEY'
});
const out = await each.predictions.run({
  model: "meta-llama-3-8b-instruct",
  version: "0.0.1",
  input: {
    "top_p": 0.9,
    "prompt": "Write a paragraph about Turkish tea",
    "max_tokens": 512,
    "min_tokens": 0,
    "temperature": 0.6,
    "prompt_template": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nYou are a helpful assistant<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
    "presence_penalty": 0,
    "frequency_penalty": 0
  },
});
console.log(out)

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Fine-tune models with your own data

You can improve open-source models with your own data to create new models that are better suited to specific tasks.

Image models like SDXL can generate images of a particular person, object, or style.

// Please make sure that you run 'npm install @eachlabs/aiflow'
import Each from '@eachlabs/aiflow';

const each = new Each({
    auth: process.env.EACH_API_KEY || 'YOUR_API_KEY'
});

const training = each.training.create("sdxl-training:13853038482995843", {
    input: {
        "input_images": "https://example.url/pictures.zip
    },
    destination: "eftal/sdxl-finetuned-with-pictures"
})

console.log(training)

// When Traning completed you can call your custom inference api 
const output = each.predictions.run("eftal/sdxl-finetuned-with-pictures", {
    input: {
        width: 512,
        height: 512,
        prompt: "a spaceship into the ocean, dramatic lights, hd",
        scheduler: "K_EULER",
        num_outputs: 1,
        guidance_scale: 7.5,
        num_inference_steps: 50
    },
})

console.log(output)

That’s it!

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Console

The easiest way! You can call public or custom model via console. Select your model and you can use ▶ Demo tab on the page.

Autoscaling and Concurrency