metadata

language:
  - en
license: apache-2.0
tags:
  - text
pretty_name: Amazon ESCI dataset in nixietune format
size_categories:
  - 100K<n<1M
source_datasets:
  - Amazon ESCI
task_categories:
  - sentence-similarity
dataset_info:
  config_name: default
  features:
    - name: query
      dtype: string
    - name: doc
      dtype: string
    - name: neg
      sequence: string
    - name: negscore
      sequence: float
  splits:
    - name: train
      num_bytes: 2734101179
      num_examples: 181819
    - name: test
      num_bytes: 1186871193
      num_examples: 79708
    - name: test_1k
      num_bytes: 16656546
      num_examples: 1000
train-eval-index:
  - config: default
    task: sentence-similarity
    splits:
      train_split: train
      eval_split: test
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train/*
      - split: test
        path: data/test/*
      - split: test_1k
        path: data/test_1k/*

Amazon ESCI dataset

A dataset in a nixietune compatible format:

{
{
  "query": "# cellist thats not a hashtag",
  "pos": "Funny Cellists That's Not A Hashtag Music Sweatshirt",
  "neg": [
    "Feelin Good Tees My Opinion Offended You Adult Humor T Shirt XL Black",
    "Christian Faith & Cross T-Shirt - Christian Faith T Shirts T-Shirt",
    "PLUS PLUS - 240 Piece Basic Mix - Construction Building Stem/Steam Toy, Mini Puzzle Blocks for Kids",
    "Caution I Learned to Drive Through Video Games - Funny Gamer T-Shirt",
    "People Who Tolerate Me On A Daily Basis T Shirt L Black",
  ]
}

This is the expanded version of the Amazon ESCI small-en dataset:

can be loaded with HF datasets directly.

Usage

from datasets import load_dataset

data = load_dataset('nixiesearch/amazon-esci', split="train")

License

Apache 2.0