task_categories:question-answering size_categories:10K<n<100K language:en license:mit region:us
---
language:
- en
license: mit
size_categories:
- 10K<n<100K
task_categories:
- question-answering
pretty_name: orca_mini_squad
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: id
    dtype: string
  - name: title
    dtype: string
  - name: context
    dtype: string
  - name: question
    dtype: string
  - name: answers
    struct:
    - name: answer_start
      dtype: int64
    - name: text
      dtype: string
  splits:
  - name: train
    num_bytes: 118261864.35315199
    num_examples: 67300
  - name: test
    num_bytes: 13140597.646848004
    num_examples: 7478
  download_size: 65276229
  dataset_size: 131402462.0
---
# Dataset Card for "orca_mini_uncensored_squad_format_train"

## Dataset Description
Mostly purely an exercise in data extraction and formatting for dataset usage, and cross-model usage of data.

Uncensored data, because when everything is sanitized for alignment, the data may be "pure" but is no longer untimately realistic.

Part of an effort to create more question-answering friendly datasets that can be used for specialized domain training on small models. 

### Dataset Summary
This is a "squad reformat" of an existing dataset located here: https://huggingface.co/datasets/julep-ai/orca_mini_uncensored

This could be swapped for squad format datasets for typical question-answering tasks with uncensored data from a partial pull of the mini-orca dataset here: psmathur/orca_minis_uncensored_dataset

### Supported Tasks and Leaderboards
- 'question-answering'

### Languages
The BCP-47 code for English as generally spoken in the United States is en-US and the BCP-47 code for English as generally spoken in the United Kingdom is en-GB. It is unknown if other varieties of English are represented in the data.

## Dataset Structure
Train and Test splits included

### Data Format
As in the squadv2 dataset, columns are: "id", "title", "context", "question", "answers": "text", "answer_start"

