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Datasets:
lajosd
/
memecoin-dataset

Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Size:
< 1K
Tags:
Synthetic
distilabel
rlaif
datacraft
Libraries:
Datasets
pandas
Dataset card Data Studio Files Community
1
memecoin-dataset
File size: 2,069 Bytes 
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---
size_categories: n<1K
task_categories:
- text-classification
dataset_info:
  features:
  - name: text
    dtype: string
  - name: label
    dtype:
      class_label:
        names:
          '0': memecoin-launch
          '1': memecoin
          '2': crypto
  splits:
  - name: train
    num_bytes: 396
    num_examples: 2
  download_size: 2267
  dataset_size: 396
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 memecoin-dataset

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/lajosd/memecoin-dataset/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/lajosd/memecoin-dataset/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


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

```json
{
    "label": 2,
    "text": "I just sold my Shiba Inu for 10x profit! I\u0027m loving the surge in demand for Dogecoin and its potential to become the next big thing. Can\u0027t wait to see the price moon and join the Wagmi crew!"
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("lajosd/memecoin-dataset", "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("lajosd/memecoin-dataset")
```


</details>