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---
language:
- en
dataset_info:
features:
- name: sentence
dtype: string
- name: cluster
dtype: int64
- name: embedding_768
sequence: float32
splits:
- name: train
num_bytes: 3106089249
num_examples: 990526
download_size: 3686385268
dataset_size: 3106089249
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "wikianswers_embeddings_768"
## Dataset Summary
`nikhilchigali/wikianswers_embeddings_768` is a subset of the `embedding-data/WikiAnswers` ([Link](https://huggingface.co/datasets/embedding-data/WikiAnswers))
As opposed to the original dataset with 3,386,256 rows, this dataset contains only .13% of the total rows(sets). The sets of sentences have been unraveled into individual items with corresponding cluster IDs to identify sentences from the same set. Each Sentence has its associated cluster ID and embeddings of dimension 768.
## Languages
English.
## Dataset Structure
Each example in the dataset contains a sentence and its cluster id of other equivalent sentences. The sentences in the same cluster are paraphrases of each other. The embeddings for the dataset are created using the `all-distilroberta-v1` model.
```
{"sentence": [sentence], "cluster": [cluster_id], "embedding_768": [embeddings]}
{"sentence": [sentence], "cluster": [cluster_id], "embedding_768": [embeddings]}
{"sentence": [sentence], "cluster": [cluster_id], "embedding_768": [embeddings]}
...
{"sentence": [sentence], "cluster": [cluster_id], "embedding_768": [embeddings]}
```
### Usage Example
Install the 🤗 Datasets library with `pip install datasets` and load the dataset from the Hub with:
```python
from datasets import load_dataset
dataset = load_dataset("nikhilchigali/wikianswers_embeddings_768")
```
The dataset is loaded as a DatasetDict and has the format for N examples:
```python
DatasetDict({
train: Dataset({
features: ['sentence', "cluster", "embedding_768"],
num_rows: N
})
})
```
Review an example i with:
```python
dataset["train"][i]
```
## Source Data
`embedding-data/WikiAnswers` on HuggingFace ([Link](https://huggingface.co/datasets/embedding-data/WikiAnswers))
### Note: This dataset is for the owner's personal use and claims no rights whatsoever.
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