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metadata
size_categories: n<1K
config_names:
  - deita_filtering
tags:
  - synthetic
  - distilabel
  - rlaif

Built with Distilabel

Dataset Card for deita-no-normalization

This dataset has been created with Distilabel.

Dataset Summary

This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:

distilabel pipeline run --config "https://huggingface.co/datasets/distilabel-internal-testing/deita-no-normalization/raw/main/pipeline.yaml"

or explore the configuration:

distilabel pipeline info --config "https://huggingface.co/datasets/distilabel-internal-testing/deita-no-normalization/raw/main/pipeline.yaml"

Dataset structure

The examples have the following structure per configuration:

Configuration: deita_filtering
{
    "answer": "The code snippet provided is correct and does not contain any logical errors.",
    "completion": "The original code counts the number of lowercase vowels in a string, but the count should probably be case-insensitive. Here is a case-insensitive version.\r\n\r\nfunction countVowels(str) {\r\n  let vowels = [\u0027a\u0027, \u0027e\u0027, \u0027i\u0027, \u0027o\u0027, \u0027u\u0027];\r\n  let count = 0;\r\n  \r\n  for (let i = 0; i \u003c str.length; i++) {\r\n    if (vowels.includes(str[i].toLowerCase())) {\r\n      count++;\r\n    }\r\n  }\r\n  \r\n return count;\r\n}",
    "conversation": [
        {
            "content": "Can you find and correct any logical errors in the following code snippet and output the corrected code?\r\n\r\nfunction countVowels(str) {\r\n  let vowels = [\u0027a\u0027, \u0027e\u0027, \u0027i\u0027, \u0027o\u0027, \u0027u\u0027];\r\n  let count = 0;\r\n  \r\n  for (let i = 0; i \u003c str.length; i++) {\r\n    if (vowels.includes(str[i])) {\r\n      count++;\r\n    }\r\n  }\r\n  \r\n  return count;\r\n}",
            "role": "user"
        },
        {
            "content": "The code snippet provided is correct and does not contain any logical errors.",
            "role": "assistant"
        }
    ],
    "deita_score": 1.0,
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        -1.22265625,
        -2.962890625
    ],
    "evol_instruction_score": 1.0,
    "evol_response_score": 1.0,
    "evolved_instruction": "Can you find and correct any logical errors in the following code snippet and output the corrected code?\r\n\r\nfunction countVowels(str) {\r\n  let vowels = [\u0027a\u0027, \u0027e\u0027, \u0027i\u0027, \u0027o\u0027, \u0027u\u0027];\r\n  let count = 0;\r\n  \r\n  for (let i = 0; i \u003c str.length; i++) {\r\n    if (vowels.includes(str[i])) {\r\n      count++;\r\n    }\r\n  }\r\n  \r\n  return count;\r\n}",
    "evolved_response": "The code snippet provided is correct and does not contain any logical errors.",
    "meta": {
        "category": "Natural language to code",
        "completion": "The original code counts the number of lowercase vowels in a string, but the count should probably be case-insensitive. Here is a case-insensitive version.\r\n\r\nfunction countVowels(str) {\r\n  let vowels = [\u0027a\u0027, \u0027e\u0027, \u0027i\u0027, \u0027o\u0027, \u0027u\u0027];\r\n  let count = 0;\r\n  \r\n  for (let i = 0; i \u003c str.length; i++) {\r\n    if (vowels.includes(str[i].toLowerCase())) {\r\n      count++;\r\n    }\r\n  }\r\n  \r\n return count;\r\n}",
        "id": 6,
        "input": null,
        "motivation_app": null,
        "prompt": "Can you find and correct any logical errors in the following code snippet and output the corrected code?\r\n\r\nfunction countVowels(str) {\r\n  let vowels = [\u0027a\u0027, \u0027e\u0027, \u0027i\u0027, \u0027o\u0027, \u0027u\u0027];\r\n  let count = 0;\r\n  \r\n  for (let i = 0; i \u003c str.length; i++) {\r\n    if (vowels.includes(str[i])) {\r\n      count++;\r\n    }\r\n  }\r\n  \r\n  return count;\r\n}",
        "source": "surge",
        "subcategory": "Debugging"
    },
    "model_name": "gpt-3.5-turbo",
    "nearest_neighbor_distance": 0.12795357273014518
}

This subset can be loaded as:

from datasets import load_dataset

ds = load_dataset("distilabel-internal-testing/deita-no-normalization", "deita_filtering")