datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
absa-quad
上述数据集为ABSA(Aspect-Based Sentiment Analysis)领域数据集，基本形式为从句子中抽取：方面术语、方面类别(术语类别)、术语在上下文中情感极性以及针对该术语的观点词，不同数据集抽取不同的信息，这点在jsonl文件的“instruction”键中有分别提到，在此我将其改造为了生成任务，需要模型按照一定格式生成抽取结果。
以acos数据集中抽取的jsonl文件一条数据举例：
{
"task_type": "generation",
"dataset": "acos",
"input": ["the computer has difficulty switching between tablet and computer ."],
"output": "[['computer', 'laptop usability', 'negative', 'difficulty']]",
"situation": "none",
"label": "",
"extra": ""… See the full description on the dataset page: https://huggingface.co/datasets/NEUDM/absa-quad.commit-messages-high-quality
Commit Messages from High-Quality Repositories
292,269 cleaned git commit messages scraped from the full histories of 15 well-regarded open-source
projects, balanced across two styles: normal (196,372) and
conventional commits (95,897).
Dataset Summary
Each record contains the commit subject, body, plus metadata: repo, sha, date,
author, and labels: style (normal/conventional), type (fix, feat, docs, ...),
scope, breaking.
Heavy cleaning: GitHub squash suffixes… See the full description on the dataset page: https://huggingface.co/datasets/Quad4/commit-messages-high-quality.ptdbench-reward-design-reward-quadratic-function-segmentation-019-dataset
PTDBench dataset snapshot: reward_quadratic_function_segmentation_019
This repository stores the immutable runtime dataset snapshot for one
materialized PTDBench task. It intentionally excludes model weights and
training checkpoints.
PTDBench family: reward_design
Source evaluation metric: eval/HELD-OUT_ENVIRONMENTS_128
Provenance: RLVE repository snapshot under its MIT license; bundled upstream benchmark notices remain applicable.
License: MIT
The artifact manifest records… See the full description on the dataset page: https://huggingface.co/datasets/LIF1014/ptdbench-reward-design-reward-quadratic-function-segmentation-019-dataset.