Andresckamilo/distilset2

---
size_categories: n<1K
dataset_info:
features:
- name: instruction
dtype: string
- name: completion
dtype: string
- name: meta
struct:
- name: category
dtype: string
- name: completion
dtype: string
- name: id
dtype: int64
- name: input
dtype: 'null'
- name: motivation_app
dtype: 'null'
- name: prompt
dtype: string
- name: source
dtype: string
- name: subcategory
dtype: string
- name: model_names
sequence: string
- name: generations
sequence: string
splits:
- name: train
num_bytes: 38944
num_examples: 10
download_size: 41785
dataset_size: 38944
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
tags:
- synthetic
- distilabel
- rlaif
---

<p align="left">
<a href="https://github.com/argilla-io/distilabel">
<img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
</a>
</p>

# Dataset Card for distilset2

This dataset has been created with [distilabel](https://distilabel.argilla.io/).

## 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:

```console
distilabel pipeline run --config "https://huggingface.co/datasets/Andresckamilo/distilset2/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/Andresckamilo/distilset2/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:

<details><summary> Configuration: default </summary><hr>

```json
{
"completion": "Denote the number of chocolates each person has by the letter of their first name. We know that\nA = D + 12\nD = R + 6\nA = 2 * R\n\nThus, A = (R + 6) + 12 = R + 18\nSince also A = 2 * R, this means 2 * R = R + 18\nHence R = 18\nHence D = 18 + 6 = 24",
"generations": [
"Given the problem, let\u0027s define:\n\n- \\( A \\) as the number of chocolates Arianna has.\n- \\( D \\) as the number of chocolates Danny has.\n- \\( R \\) as the number of chocolates Robbie has.\n\nAccording to the problem, we have the following relationships:\n\n1. \\( A = D + 12 \\) (Arianna has 12 chocolates more than Danny).\n2. \\( D = R + 6 \\) (Danny has 6 chocolates more than Robbie).\n3. \\( A = 2R \\) (Arianna has twice as many chocolates as Robbie).\n\nWe need to determine the number of chocolates Danny has, \\( D \\).\n\nFirst, let\u0027s express \\( A \\) in terms of \\( R \\) using the third relationship:\n\\[ A = 2R \\]\n\nNext, substitute \\( A = 2R \\) into the first relationship \\( A = D + 12 \\):\n\\[ 2R = D + 12 \\]\n\nNow we can solve for \\( D \\):\n\\[ D = 2R - 12 \\]\n\nWe also know from the second relationship that \\( D = R + 6 \\). So we can set the two expressions for \\( D \\) equal to each other:\n\\[ 2R - 12 = R + 6 \\]\n\nSolving for \\( R \\):\n\\[ 2R - R = 6 + 12 \\]\n\\[ R = 18 \\]\n\nNow that we have \\( R = 18 \\), we can find \\( D \\) using \\( D = R + 6 \\):\n\\[ D = 18 + 6 \\]\n\\[ D = 24 \\]\n\nThus, Danny has \\( 24 \\) chocolates.",
"Let\u0027s denote the number of chocolates that Robbie has as R.\n\nAccording to the problem, Arianna has twice as many chocolates as Robbie, so Arianna has 2R chocolates.\n\nDanny has 6 chocolates more than Robbie, so Danny has R + 6 chocolates.\n\nArianna has 12 chocolates more than Danny, so we can set up the equation 2R = R + 6 + 12.\n\nSimplifying the equation, we get 2R = R + 18.\n\nSubtracting R from both sides, we get R = 18.\n\nSo, Danny has R + 6 = 18 + 6 = 24 chocolates.\n\nThe answer is: 24",
null
],
"instruction": "Arianna has 12 chocolates more than Danny. Danny has 6 chocolates more than Robbie. Arianna has twice as many chocolates as Robbie has. How many chocolates does Danny have?",
"meta": {
"category": "Question Answering",
"completion": "Denote the number of chocolates each person has by the letter of their first name. We know that\nA = D + 12\nD = R + 6\nA = 2 * R\n\nThus, A = (R + 6) + 12 = R + 18\nSince also A = 2 * R, this means 2 * R = R + 18\nHence R = 18\nHence D = 18 + 6 = 24",
"id": 0,
"input": null,
"motivation_app": null,
"prompt": "Arianna has 12 chocolates more than Danny. Danny has 6 chocolates more than Robbie. Arianna has twice as many chocolates as Robbie has. How many chocolates does Danny have?",
"source": "surge",
"subcategory": "Math"
},
"model_names": [
"gpt-4o",
"deepseek-chat",
null
]
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("Andresckamilo/distilset2", "default")
```

Or simply as it follows, since there's only one configuration and is named `default`:

```python
from datasets import load_dataset

ds = load_dataset("Andresckamilo/distilset2")
```

</details>

原始信息汇总

数据集卡片 for distilset2

数据集概述

该数据集包含一个 pipeline.yaml 文件，可以使用 distilabel CLI 在 distilabel 中重现生成该数据集的管道：

console distilabel pipeline run --config "https://huggingface.co/datasets/Andresckamilo/distilset2/raw/main/pipeline.yaml"

或者探索配置：

console distilabel pipeline info --config "https://huggingface.co/datasets/Andresckamilo/distilset2/raw/main/pipeline.yaml"

数据集结构

每个配置的示例具有以下结构：

<details><summary> 配置: default </summary><hr>

json { "completion": "Denote the number of chocolates each person has by the letter of their first name. We know that A = D + 12 D = R + 6 A = 2 * R

Thus, A = (R + 6) + 12 = R + 18 Since also A = 2 * R, this means 2 * R = R + 18 Hence R = 18 Hence D = 18 + 6 = 24", "generations": [ "Given the problem, letu0027s define:

• ( A ) as the number of chocolates Arianna has.
• ( D ) as the number of chocolates Danny has.
• ( R ) as the number of chocolates Robbie has.

According to the problem, we have the following relationships:

1. ( A = D + 12 ) (Arianna has 12 chocolates more than Danny).
2. ( D = R + 6 ) (Danny has 6 chocolates more than Robbie).
3. ( A = 2R ) (Arianna has twice as many chocolates as Robbie).

We need to determine the number of chocolates Danny has, ( D ).

First, letu0027s express ( A ) in terms of ( R ) using the third relationship: [ A = 2R ]

Next, substitute ( A = 2R ) into the first relationship ( A = D + 12 ): [ 2R = D + 12 ]

Now we can solve for ( D ): [ D = 2R - 12 ]

We also know from the second relationship that ( D = R + 6 ). So we can set the two expressions for ( D ) equal to each other: [ 2R - 12 = R + 6 ]

Solving for ( R ): [ 2R - R = 6 + 12 ] [ R = 18 ]

Now that we have ( R = 18 ), we can find ( D ) using ( D = R + 6 ): [ D = 18 + 6 ] [ D = 24 ]

Thus, Danny has ( 24 ) chocolates.", "Letu0027s denote the number of chocolates that Robbie has as R.

According to the problem, Arianna has twice as many chocolates as Robbie, so Arianna has 2R chocolates.

Danny has 6 chocolates more than Robbie, so Danny has R + 6 chocolates.

Arianna has 12 chocolates more than Danny, so we can set up the equation 2R = R + 6 + 12.

Simplifying the equation, we get 2R = R + 18.

Subtracting R from both sides, we get R = 18.

So, Danny has R + 6 = 18 + 6 = 24 chocolates.

The answer is: 24", null ], "instruction": "Arianna has 12 chocolates more than Danny. Danny has 6 chocolates more than Robbie. Arianna has twice as many chocolates as Robbie has. How many chocolates does Danny have?", "meta": { "category": "Question Answering", "completion": "Denote the number of chocolates each person has by the letter of their first name. We know that A = D + 12 D = R + 6 A = 2 * R

Thus, A = (R + 6) + 12 = R + 18 Since also A = 2 * R, this means 2 * R = R + 18 Hence R = 18 Hence D = 18 + 6 = 24", "id": 0, "input": null, "motivation_app": null, "prompt": "Arianna has 12 chocolates more than Danny. Danny has 6 chocolates more than Robbie. Arianna has twice as many chocolates as Robbie has. How many chocolates does Danny have?", "source": "surge", "subcategory": "Math" }, "model_names": [ "gpt-4o", "deepseek-chat", null ] }

该子集可以加载为：

python from datasets import load_dataset

ds = load_dataset("Andresckamilo/distilset2", "default")

或者简单地加载，因为只有一个配置并且命名为 default：

python from datasets import load_dataset

ds = load_dataset("Andresckamilo/distilset2")

</details>