README.md

---
dataset_info:
  features:
  - name: sentence
    dtype: string
  - name: cluster
    dtype: int64
  - name: embedding_384
    sequence: float32
  splits:
  - name: train
    num_bytes: 1584641313
    num_examples: 990526
  download_size: 2163024841
  dataset_size: 1584641313
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
task_categories:
- sentence-similarity
language:
- en
size_categories:
- 100K<n<1M
---

# Dataset Card for "wikianswers_embeddings_384"
## Dataset Summary
`nikhilchigali/wikianswers_embeddings_384` 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 384.

## 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-MiniLM-L6-v2` model.
```
{"sentence": [sentence], "cluster": [cluster_id], "embedding_384": [embeddings]}
{"sentence": [sentence], "cluster": [cluster_id], "embedding_384": [embeddings]}
{"sentence": [sentence], "cluster": [cluster_id], "embedding_384": [embeddings]}
...
{"sentence": [sentence], "cluster": [cluster_id], "embedding_384": [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_384")
```

The dataset is loaded as a DatasetDict and has the format for N examples:

```python
DatasetDict({
    train: Dataset({
        features: ['sentence', "cluster", "embedding_384"],
        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.