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README.md
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---
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dataset_info:
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features:
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- name: text
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data_files:
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- split: train
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path: data/train-*
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---
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---
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size_categories: n<1K
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task_categories:
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- text-classification
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dataset_info:
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features:
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- name: text
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data_files:
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- split: train
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path: data/train-*
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tags:
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- synthetic
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- distilabel
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- rlaif
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- datacraft
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---
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<p align="left">
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<a href="https://github.com/argilla-io/distilabel">
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<img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
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</a>
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</p>
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# Dataset Card for my-distiset-a74405a0
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This dataset has been created with [distilabel](https://distilabel.argilla.io/).
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## Dataset Summary
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This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI:
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```console
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distilabel pipeline run --config "https://huggingface.co/datasets/sho2025/my-distiset-a74405a0/raw/main/pipeline.yaml"
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```
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or explore the configuration:
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```console
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distilabel pipeline info --config "https://huggingface.co/datasets/sho2025/my-distiset-a74405a0/raw/main/pipeline.yaml"
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```
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## Dataset structure
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The examples have the following structure per configuration:
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<details><summary> Configuration: default </summary><hr>
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```json
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{
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"label": 5,
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"text": "John Smith was born on August 12, 1990, in New York City. He holds a Bachelor\u0027s degree in Computer Science from Columbia University and a Master\u0027s degree in Data Science from Stanford University. His address is 123 Main Street, but we can only meet him at the designated meeting point. His phone number is not available as it is for personal use only."
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}
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```
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This subset can be loaded as:
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```python
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from datasets import load_dataset
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ds = load_dataset("sho2025/my-distiset-a74405a0", "default")
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```
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Or simply as it follows, since there's only one configuration and is named `default`:
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```python
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from datasets import load_dataset
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ds = load_dataset("sho2025/my-distiset-a74405a0")
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```
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</details>
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