davanstrien/similarity-dataset-test
收藏Hugging Face2024-05-24 更新2024-06-12 收录
下载链接:
https://hf-mirror.com/datasets/davanstrien/similarity-dataset-test
下载链接
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资源简介:
---
size_categories: n<1K
dataset_info:
features:
- name: anchor
dtype: string
- name: positive
dtype: string
- name: negative
dtype: string
- name: generation
dtype: string
splits:
- name: train
num_bytes: 315140
num_examples: 400
download_size: 127797
dataset_size: 315140
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 similarity-dataset-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/davanstrien/similarity-dataset-test/raw/main/pipeline.yaml"
```
or explore the configuration:
```console
distilabel pipeline info --config "https://huggingface.co/datasets/davanstrien/similarity-dataset-test/raw/main/pipeline.yaml"
```
## Dataset structure
The examples have the following structure per configuration:
<details><summary> Configuration: default </summary><hr>
```json
{
"anchor": "$BYND - JPMorgan reels in expectations on Beyond Meat https://t.co/bd0xbFGjkT",
"generation": "{\n \"bad\": [\n \"Beyond Meat\u0027s stock price takes a hit as JPMorgan lowers expectations\",\n \"JPMorgan\u0027s downgrade of Beyond Meat sends shares tumbling\",\n \"Investors disappointed as JPMorgan cuts Beyond Meat\u0027s outlook\"\n ],\n \"good\": [\n \"JPMorgan reduces forecasts for Beyond Meat, causing concern among investors\",\n \"Beyond Meat\u0027s future looks less promising as JPMorgan adjusts expectations\",\n \"JPMorgan\u0027s revised outlook dampens enthusiasm for Beyond Meat\u0027s stock\"\n ]\n}",
"negative": "Beyond Meat\u0027s stock price takes a hit as JPMorgan lowers expectations",
"positive": "JPMorgan\u0027s revised outlook dampens enthusiasm for Beyond Meat\u0027s stock"
}
```
This subset can be loaded as:
```python
from datasets import load_dataset
ds = load_dataset("davanstrien/similarity-dataset-test", "default")
```
Or simply as it follows, since there's only one configuration and is named `default`:
```python
from datasets import load_dataset
ds = load_dataset("davanstrien/similarity-dataset-test")
```
</details>
提供机构:
davanstrien
原始信息汇总
数据集概述
数据集信息
- 大小分类: n<1K
- 特征:
- anchor: 字符串类型
- positive: 字符串类型
- negative: 字符串类型
- generation: 字符串类型
- 分割:
- train:
- num_bytes: 315140
- num_examples: 400
- train:
- 下载大小: 127797
- 数据集大小: 315140
配置
- config_name: default
- data_files:
- split: train
- path: data/train-*
标签
- synthetic
- distilabel
- rlaif
数据集结构
- 配置: default
- 结构: json { "anchor": "$BYND - JPMorgan reels in expectations on Beyond Meat https://t.co/bd0xbFGjkT", "generation": "{ "bad": [ "Beyond Meatu0027s stock price takes a hit as JPMorgan lowers expectations", "JPMorganu0027s downgrade of Beyond Meat sends shares tumbling", "Investors disappointed as JPMorgan cuts Beyond Meatu0027s outlook" ], "good": [ "JPMorgan reduces forecasts for Beyond Meat, causing concern among investors", "Beyond Meatu0027s future looks less promising as JPMorgan adjusts expectations", "JPMorganu0027s revised outlook dampens enthusiasm for Beyond Meatu0027s stock" ] }", "negative": "Beyond Meatu0027s stock price takes a hit as JPMorgan lowers expectations", "positive": "JPMorganu0027s revised outlook dampens enthusiasm for Beyond Meatu0027s stock" }
加载数据集
python from datasets import load_dataset
ds = load_dataset("davanstrien/similarity-dataset-test", "default")
或者,由于只有一个配置且名为default,可以直接加载:
python
from datasets import load_dataset
ds = load_dataset("davanstrien/similarity-dataset-test")



