metadata
dataset_info:
features:
- name: set
sequence: string
splits:
- name: train
num_bytes: 1580895690.1875737
num_examples: 1095326
download_size: 665292967
dataset_size: 1580895690.1875737
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
task_categories:
- feature-extraction
- text-classification
- sentence-similarity
language:
- en
size_categories:
- 1M<n<10M
Dataset Card for "WikiAnswers Small"
Dataset Summary
nikhilchigali/wikianswers_small
is a subset of the embedding-data/WikiAnswers
dataset (Link). This dataset is for the owner's personal use and claims no rights whatsoever.
As opposed to the original dataset with 3,386,256
rows, this dataset contains only 4% of the total rows (1,095,326).
Languages
English.
Dataset Structure
Each example in the dataset contains 25 equivalent sentences and is formatted as a dictionary with the key "set" and a list with the sentences as "value".
{"set": [sentence_1, sentence_2, ..., sentence_25]}
{"set": [sentence_1, sentence_2, ..., sentence_25]}
...
{"set": [sentence_1, sentence_2, ..., sentence_25]}
Usage Example
Install the 🤗 Datasets library with pip install datasets
and load the dataset from the Hub with:
from datasets import load_dataset
dataset = load_dataset("embedding-data/WikiAnswers")
The dataset is loaded as a DatasetDict
and has the format for N
examples:
DatasetDict({
train: Dataset({
features: ['set'],
num_rows: N
})
})
Review an example i
with:
dataset["train"][i]["set"]
Source Data
embedding-data/WikiAnswers
on HuggingFace (Link)