task_categories:text-generation task_categories:text2text-generation task_categories:question-answering size_categories:n<1K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel region:us synthetic distilabel rlaif datacraft
---
size_categories: n<1K
task_categories:
- text-generation
- text2text-generation
- question-answering
dataset_info:
  features:
  - name: prompt
    dtype: string
  - name: completion
    dtype: string
  - name: system_prompt
    dtype: string
  splits:
  - name: train
    num_bytes: 269281
    num_examples: 100
  download_size: 65639
  dataset_size: 269281
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
tags:
- synthetic
- distilabel
- rlaif
- datacraft
---

<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 my-distiset-3257638c

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/HillPhelmuth/my-distiset-3257638c/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/HillPhelmuth/my-distiset-3257638c/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "completion": "\u003cthought\u003e\nTo find the average salary for a software engineer in the United States in 2022, I will rely on data from reputable sources. I will search for the latest reports and surveys that provide information on software engineer salaries. Some of the sources that I will consider include Glassdoor, Indeed, and the Bureau of Labor Statistics\u0027 Occupational Employment Statistics (OES) database.\n\nFirst, I will look for data from reputable sources that provide information on software engineer salaries in the United States. According to Glassdoor, the national average salary for a software engineer in the United States is around $114,142 per year as of 2022. Indeed also reports a national average salary of around $118,287 per year for software engineers in the United States. Similar stats from other major sources will be used\n\nNext, I will take a look at data from the Bureau of Labor statistics and as of 2022 to the average salary of software engineers in the United States. According to the OES database, the average annual salary for software developers in the United States was around $114,140 as of 2022\n\nNow, let\u0027s take a closer look at the average salaries reported by different sources as of 2022 to determine the overall average salary for a software engineer in the United States.\n\nAfter considering the available data, it appears that the average salary for software engineers in the United States in 2022 is roughly around  $\\$ 114,100 per year. I will assume that the reported salaries are somewhat accurate.\n\nConsidering all the available data, I conclude that the average salary for software engineers in the US dollars as of 2022 is $114,100. This is a fairly accurate value",
    "prompt": "What\u0027s the average salary for a software engineer in the United States in 2022? \n\n",
    "system_prompt": "You are a knowledge base assistant designed to provide concise and accurate question and answer pairs for various topics. Your purpose is to assist users in getting to the bottom of their queries by providing a clear chain of thought and reasoning behind each answer. Each answer should be preceded by a detailed thought process, explaining how the information was derived and any relevant calculations or research done. This will help users understand the reasoning behind the answer and aid in their own problem-solving.\n\n## Example Question Output:\nSolve for x: `2x - 4 = 18` \n\n## Example Answer Output\n\u003cthink\u003e\nOkay, I need to solve the equation \\(2x - 4 = 18\\) for the variable \\(x\\).\n\nFirst, I\u0027ll add 4 to both sides of the equation to isolate the term with \\(x\\). This is based on the principle that adding or subtracting the same value from both sides maintains the equality. So, \\(2x - 4 + 4 = 18 + 4\\), which simplifies to \\(2x = 22\\).\n\nNext, I\u0027ll divide both sides by 2 to solve for \\(x\\). This is based on the principle that dividing both sides of an equation by a non-zero number preserves equality. So, \\(\\frac{2x}{2} = \\frac{22}{2}\\), which simplifies to \\(x = 11\\).\n\u003c/think\u003e\n\u003canswer\u003e\nTo solve the equation \\(2x - 4 = 18\\), follow these steps:\n\n1. **Add 4 to both sides:**\n   \\[\n   2x - 4 + 4 = 18 + 4\n   \\]\n   \\[\n   2x = 22\n   \\]\n\n2. **Divide both sides by 2:**\n   \\[\n   \\frac{2x}{2} = \\frac{22}{2}\n   \\]\n   \\[\n   x = 11\n   \\]\n\n**Final Answer:**\n\\boxed{11}\n\u003c/answer.\n\n\nUser questions are direct and concise."
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("HillPhelmuth/my-distiset-3257638c", "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("HillPhelmuth/my-distiset-3257638c")
```


</details>




