aexol-studio/recommendation_hybrid

aexol-studio / recommendation_hybrid

Public
68 runs

Run aexol-studio/recommendation_hybrid with an API

Use one of our client libraries to get started quickly. Clicking on a library will take you to the Playground tab where you can tweak different inputs, see the results, and copy the corresponding code to use in your own project.

Input schema

The fields you can use to run this model with an API. If you don't give a value for a field its default value will be used.

Field	Type	Default value	Description
data	string	api:McAuley-Lab/Amazon-Reviews-2023 raw_review_Subscription_Boxes	HuggingFace Dataset API (api:McAuley-Lab/Amazon-Reviews-2023 raw_review_Magazine_Subscriptions) or path (path:data/reviews.csv)
user_id	string	AHZKJ74LZJQMNNPISIOTL36TXDIA	User id
user_column	string	user_id	Column storing the user ids
name_column	string	title	Column storing the name of the items
text_column	string	text	Column storing the reviews or descriptions of the items
item_column	string	parent_asin	Column storing the items ids
top_n	integer	10	Number of top recommendation to return
prediction	string (enum)	items Options: items, users, both	Prediction type: items (only items), users (only users), both (items and users)
pretrained	boolean	False	Whether to use a pretrained models
show_metrics	boolean	False	Whether to show the evaluation metrics

{
  "type": "object",
  "title": "Input",
  "properties": {
    "data": {
      "type": "string",
      "title": "Data",
      "default": "api:McAuley-Lab/Amazon-Reviews-2023 raw_review_Subscription_Boxes",
      "x-order": 0,
      "description": "HuggingFace Dataset API (api:McAuley-Lab/Amazon-Reviews-2023 raw_review_Magazine_Subscriptions) or path (path:data/reviews.csv)"
    },
    "top_n": {
      "type": "integer",
      "title": "Top N",
      "default": 10,
      "x-order": 6,
      "description": "Number of top recommendation to return"
    },
    "user_id": {
      "type": "string",
      "title": "User Id",
      "default": "AHZKJ74LZJQMNNPISIOTL36TXDIA",
      "x-order": 1,
      "description": "User id"
    },
    "prediction": {
      "enum": [
        "items",
        "users",
        "both"
      ],
      "type": "string",
      "title": "prediction",
      "description": "Prediction type: items (only items), users (only users), both (items and users)",
      "default": "items",
      "x-order": 7
    },
    "pretrained": {
      "type": "boolean",
      "title": "Pretrained",
      "default": false,
      "x-order": 8,
      "description": "Whether to use a pretrained models"
    },
    "item_column": {
      "type": "string",
      "title": "Item Column",
      "default": "parent_asin",
      "x-order": 5,
      "description": "Column storing the items ids"
    },
    "name_column": {
      "type": "string",
      "title": "Name Column",
      "default": "title",
      "x-order": 3,
      "description": "Column storing the name of the items"
    },
    "text_column": {
      "type": "string",
      "title": "Text Column",
      "default": "text",
      "x-order": 4,
      "description": "Column storing the reviews or descriptions of the items"
    },
    "user_column": {
      "type": "string",
      "title": "User Column",
      "default": "user_id",
      "x-order": 2,
      "description": "Column storing the user ids"
    },
    "show_metrics": {
      "type": "boolean",
      "title": "Show Metrics",
      "default": false,
      "x-order": 9,
      "description": "Whether to show the evaluation metrics"
    }
  }
}

Output schema

The shape of the response you’ll get when you run this model with an API.

Schema

{
  "type": "string",
  "title": "Output"
}