aexol-studio / recommendation_user_based

  • Public
  • 50 runs
  • T4
Iterate in playground

Input

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

npx create-replicate --model=aexol-studio/recommendation_user_based
or set up a project from scratch
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 aexol-studio/recommendation_user_based using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "aexol-studio/recommendation_user_based:75bbe961c3e6986824e87874cdbd1bb738d02aaba43b299b45828b4719992bb3",
  {
    input: {
      data: "api:McAuley-Lab/Amazon-Reviews-2023 0core_rating_only_Digital_Music",
      size: 10,
      max_rating: 5,
      min_rating: 1,
      pretrained: false,
      line_format: "user item rating timestamp",
      columns_name: "user_id parent_asin rating",
      show_metrics: false
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Output

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

Run time and cost

This model runs on Nvidia T4 GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

This model doesn't have a readme.