datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
bimanual-table-cleanup-cross-embodiment-rich-modality-sample
Cross-Embodiment Bimanual Table Cleanup — Rich-Modality 10-Episode Inspection Sample
10 full-modality cross-embodiment bimanual table-cleanup episodes: 5 Franka Panda + 5 WidowXAI, 21,267 frames, 6 RGB views per robot, task-camera depth and segmentation, native robot state/action, end-effector trajectories, 6-DoF object poses, and QA annotations.
✅ Use it / ❌ Skip it
Use it for
Inspecting loaders, schemas, camera coverage, depth, segmentation, object poses… See the full description on the dataset page: https://huggingface.co/datasets/ExylosAi/bimanual-table-cleanup-cross-embodiment-rich-modality-sample.object-sorting-cross-embodiment-rich-modality-sample
Cross-Embodiment Object Sorting — Rich-Modality 20-Episode Inspection Sample
20 episodes total: 10 Franka Panda + 10 WidowXAI. A compact cross-embodiment inspection release for picking up an instructed object and placing it into an instructed target box. Each robot keeps its native LeRobot v2.1 state/action schema in a separate Viewer config. Five synchronized RGB views, metric depth and instance segmentation for every camera, robot state/action, end-effector trajectories… See the full description on the dataset page: https://huggingface.co/datasets/ExylosAi/object-sorting-cross-embodiment-rich-modality-sample.coffee-brew-cross-embodiment-rich-modality-sample
Cross-Embodiment Coffee Brew — Rich-Modality 10-Episode Inspection Sample
10 full-modality cross-embodiment coffee-brew episodes: 5 single-arm Franka Panda + 5 single-arm WidowXAI, 14,401 frames, 5 RGB views per robot, task-camera depth and segmentation, native robot state/action, end-effector trajectories, 6-DoF object poses, and QA annotations.
✅ Use it / ❌ Skip it
Use it for
Inspecting loaders, schemas, camera coverage, depth, segmentation, object poses… See the full description on the dataset page: https://huggingface.co/datasets/ExylosAi/coffee-brew-cross-embodiment-rich-modality-sample.Swift-OpenX-Embodiment-wrist-imagesthe-Embodiment-of-Scarlet-Devil-Instruct-Alpaca-QA-JP-v1
Converted QA Dataset
このデータセットは、easy-dataset-cliを使用して生成されたアルパカ形式の日本語Q&Aデータセットです。
データセット概要
総エントリ数: 97,202
形式: Alpaca形式
言語: 日本語
ライセンス: MIT
データ構造
各エントリは以下の形式です：
{
"instruction": "質問文",
"input": "",
"output": "回答文",
"genre": "ジャンル",
"audience": "対象読者"
}
ジャンル分布
含まれるジャンル:
FAQ
PRD
RFP/提案書
アーキレビュー
エグゼクティブサマリ
ガイドライン/ポリシー
ケーススタディ
セキュリティレビュー
チュートリアル
ハンズオン課題
ベストプラクティス集
ワークショップ資料
実験レポート
対話形式
技術ブログ
教科書
業界別ケーススタディ
法務チェックリスト
運用Runbook
対象読者分布… See the full description on the dataset page: https://huggingface.co/datasets/MakiAi/the-Embodiment-of-Scarlet-Devil-Instruct-Alpaca-QA-JP-v1.