datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
video_agent_trace
Friday prompt delivery — 30K text-only corpus
本目录是可直接消费的 prompt 交付包；所有内容均来自已完成的 Friday GPT 文本生产，不包含视频，也不表示 H3/视频评测通过。
文件
文件
内容
top_historical_test_prompts_4of5.jsonl
第一轮多轮历史实验中全局最高接受率的两条 test prompt（各 4/5）。
family_champion_test_prompts.jsonl
四个家族各自采用的 champion test prompt；包含 4/5、4/5、3/5、3/5 的历史结果与选择理由。
base_prompts_1200.jsonl
1,200 条干净 base prompt，每条有稳定 base_id。
injection_prompts_30000.jsonl
30,000 条最终 injection prompt；prompt 是可直接读取的 prompt… See the full description on the dataset page: https://huggingface.co/datasets/ppppppz/video_agent_trace.PyVision-Video-RL-Data
PyVision-Video-RL-Data
Project Page | Paper | GitHub
This repository contains the reinforcement learning (RL) data used to train PyVision-Video-RL, as presented in the paper PyVision-RL: Forging Open Agentic Vision Models via RL.
PyVision-RL is a reinforcement learning framework for open-weight multimodal models that stabilizes training and sustains interaction. For video reasoning, PyVision-Video employs on-demand context construction, selectively sampling task-relevant frames… See the full description on the dataset page: https://huggingface.co/datasets/Agents-X/PyVision-Video-RL-Data.video-generator-ai-agent
Video Generator Agent Meta and Traffic Dataset in AI Agent Marketplace | AI Agent Directory | AI Agent Index from DeepNLP
This dataset is collected from AI Agent Marketplace Index and Directory at http://www.deepnlp.org, which contains AI Agents's meta information such as agent's name, website, description, as well as the monthly updated Web performance metrics, including Google,Bing average search ranking positions, Github Stars, Arxiv References, etc.
The dataset is helpful for AI… See the full description on the dataset page: https://huggingface.co/datasets/DeepNLP/video-generator-ai-agent.video_debug_agent_2
dataset_v1_packed — 视频生成缺陷标注数据集
每条样本 = 一个视频生成 case：生成需求(input_text) + 参考素材(input_media) + 成片(output_media) + 缺陷标注(label)。
Schema
字段
说明
id
样本编号
input_text
视频生成需求脚本（分镜/提示词）
input_media
参考素材相对路径，顺序为 图→视频→音频
output_media
生成成片相对路径
label
缺陷标注串：<interval>起-止</interval><tag>大类:小类</tag><feedback>缺陷描述</feedback> × N
687 条样本；标签体系为 8 大类 / 31 小类闭集。
interval 单位秒，保留 1 位小数，按时间升序。
用途
仅限学术研究。媒体素材为短剧成片画面，请勿再分发。
rl_data_vsi_filtered_wo_video_hintrl_data_longvila_filtered_wo_video_hint