license:mit region:us
---
license: mit
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validate
    path: data/validate-*
dataset_info:
  features:
  - name: command
    dtype: string
  - name: description
    dtype: string
  - name: syntax
    dtype: string
  - name: flags
    dtype: string
  - name: code
    dtype: string
  - name: cot
    dtype: string
  - name: question
    dtype: string
  splits:
  - name: train
    num_bytes: 4665440
    num_examples: 3161
  - name: validate
    num_bytes: 464502
    num_examples: 316
  download_size: 281693
  dataset_size: 5129942
---

# Dataset
The dataset is scraped from: https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands  
The program names, the syntax, the flags and the description, and the examples with the example description and the example code are scraped

The Cot field that describes why does the parameters used in the 'example code' will do what the 'example description' asks is generated using gpt-3.5-turbo  
The questions for the example code, description pairs are generated using gpt-4  
