metadata

language:
  - en
license: apache-2.0
tags:
  - text
pretty_name: MS MARCO dummy dataset
size_categories:
  - 100K<n<1M
source_datasets:
  - MSMARCO
task_categories:
  - sentence-similarity
dataset_info:
  config_name: default
  features:
    - name: query
      dtype: string
    - name: positive
      sequence: string
    - name: negative
      sequence: string
  splits:
    - name: train
      num_bytes: 11535280
      num_examples: 1000
    - name: test
      num_bytes: 11668968
      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/*

MS MARCO dummy+test dataset

Used for testing nixietune: a dummy dataset of random 1000 queries from MS MARCO. The format is the following:

{
  "query": ")what was the immediate impact of the success of the manhattan project?",
  "positive": [
      "The presence of communication amid scientific minds was equally important to the success of the Manhattan Project as scientific intellect was. The only cloud hanging over the impressive achievement of the atomic researchers and engineers is what their success truly meant; hundreds of thousands of innocent lives obliterated."
  ],
  "negative": []
}

Usage

from datasets import load_dataset

data = load_dataset('nixiesearch/ms-marco-dummy')
print(data["train"].features)

License

Apache 2.0