YYYYYYibo/ultrafeedback_binarized_new_gen_part_3
收藏Hugging Face2024-05-06 更新2024-06-12 收录
下载链接:
https://hf-mirror.com/datasets/YYYYYYibo/ultrafeedback_binarized_new_gen_part_3
下载链接
链接失效反馈官方服务:
资源简介:
---
dataset_info:
features:
- name: prompt
dtype: string
- name: prompt_id
dtype: string
- name: chosen
list:
- name: content
dtype: string
- name: role
dtype: string
- name: rejected
list:
- name: content
dtype: string
- name: role
dtype: string
- name: messages
list:
- name: content
dtype: string
- name: role
dtype: string
- name: score_chosen
dtype: float64
- name: score_rejected
dtype: float64
- name: reference_response
dtype: string
splits:
- name: train_prefs
num_bytes: 42115228
num_examples: 5000
download_size: 23156523
dataset_size: 42115228
configs:
- config_name: default
data_files:
- split: train_prefs
path: data/train_prefs-*
---
# Dataset Card for "ultrafeedback_binarized_new_gen_part_3"
[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
The dataset includes multiple features such as prompt, prompt_id, chosen, rejected, messages, score_chosen, score_rejected, and reference_response. Among them, chosen and rejected contain two sub-features: content and role, and messages also contain content and role. The dataset is divided into a training set named train_prefs, containing 5000 samples. The download size of the dataset is 23156523 bytes, and the total size is 42115228 bytes. The dataset configuration is named default, and the data file path is data/train_prefs-*.
提供机构:
YYYYYYibo
原始信息汇总
数据集概述
数据集名称
ultrafeedback_binarized_new_gen_part_3
数据集特征
- prompt: 字符串类型
- prompt_id: 字符串类型
- chosen:
- content: 字符串类型
- role: 字符串类型
- rejected:
- content: 字符串类型
- role: 字符串类型
- messages:
- content: 字符串类型
- role: 字符串类型
- score_chosen: 浮点数类型(float64)
- score_rejected: 浮点数类型(float64)
- reference_response: 字符串类型
数据集划分
- train_prefs:
- 数据大小: 42115228字节
- 示例数量: 5000
数据集大小
- 下载大小: 23156523字节
- 数据集大小: 42115228字节
配置
- config_name: default
- data_files:
- split: train_prefs
- path: data/train_prefs-*



