gabrielmbmb/test
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--- size_categories: n<1K config_names: - to_argilla 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 test 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/gabrielmbmb/test/raw/main/pipeline.yaml" ``` or explore the configuration: ```console distilabel pipeline info --config "https://huggingface.co/datasets/gabrielmbmb/test/raw/main/pipeline.yaml" ``` ## Dataset structure The examples have the following structure per configuration: <details><summary> Configuration: to_argilla </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", "generation": "Let\u0027s use variables to represent the number of chocolates each person has:\n\nLet x be the number of chocolates Robbie has.\nThen Danny has x + 6 chocolates.\nAnd Arianna has x + 6 + 12 = x + 18 chocolates.\n\nGiven that Arianna has twice as many chocolates as Robbie, we can write the equation:\nx + 18 = 2x\n\nSolving for x:\nx = 18\n\nSo, Robbie has 18 chocolates, Danny has 18 + 6 = 24 chocolates.", "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_name": "gpt-3.5-turbo" } ``` This subset can be loaded as: ```python from datasets import load_dataset ds = load_dataset("gabrielmbmb/test", "to_argilla") ``` </details>
数据集概述
数据集基本信息
- 名称: test
- 创建工具: Distilabel
- 大小分类: n<1K
- 配置名称: to_argilla
- 标签: synthetic, distilabel, rlaif
数据集内容
- 结构: 包含一个
pipeline.yaml文件，用于在distilabel中重现生成此数据集的管道。 - 示例结构: 每个配置的示例包含
completion,generation,instruction,meta和model_name字段。
数据集使用
- 重现管道: 使用
distilabelCLI执行pipeline.yaml文件。 - 加载数据集: 通过
datasets库加载特定配置的数据集。
python from datasets import load_dataset
ds = load_dataset("gabrielmbmb/test", "to_argilla")
