datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
sft_alfworld_trajectory_dataset_v5
ALFWorld Trajectory Dataset
Overview
This is a synthetic SFT (Supervised Fine-Tuning) dataset designed for agent training in ALFWorld-compatible environments. The dataset programmatically generates expert trajectories without requiring an actual ALFWorld environment or a large language model.
Key Approach
Template-based Simulation: Lightweight simulator based on published ALFWorld information (papers, ReAct prompt examples).
Subgoal Decomposition: Rule-based… See the full description on the dataset page: https://huggingface.co/datasets/u-10bei/sft_alfworld_trajectory_dataset_v5.Agent-Trajectory-Data-Sample
Agent-Trajectory-Dataset
Description
This dataset covers office-based scenarios such as in-depth searches, data analysis, and industry research, encompassing complete multi-turn reasoning trajectories and tool-calling chains. It is designed to support the analysis of agent planning capabilities, research into tool selection strategies, and quality assessment, providing a structured benchmark for agent training and evaluation.
For more details, please refer to the… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata-AI/Agent-Trajectory-Data-Sample.Agent-Trajectory-Dataset
Description
본 데이터셋은 심층 검색, 데이터 분석, 산업 리서치 등 사무 환경에서 수행되는 다양한 작업 시나리오를 포함하며, 완전한 멀티턴 추론 과정과 도구 호출 체인으로 구성되어 있습니다. 에이전트의 계획 수립 능력 분석, 도구 선택 전략 연구 및 작업 품질 평가를 지원하도록 설계되었으며, 에이전트 학습 및 평가를 위한 구조화된 벤치마크로 활용할 수 있습니다.
자세한 내용은 아래 링크를 참고해 주세요: https://ko.nexdata.ai/datasets/llm/2185?source=hf.kr
Specifications
Data content
OpenClaw를 통해 생성된 에이전트 트래젝토리 데이터
Category
심층 검색, 데이터 분석, 산업 리서치
Data volume
5,300
Model… See the full description on the dataset page: https://huggingface.co/datasets/Nexdata-kr/Agent-Trajectory-Dataset.deterministic-trajectory-transitions-25k
ASE Syntax Extractions
The machine does not dream. It computes — and in that computation, structure emerges. This is not simulated data; it is an extraction of axiomatic necessity.
Overview
This dataset contains deterministic trajectory extractions from a closed, axiomatic system. Every frame is the output of a syntax engine where (seed, tick, entity) tuples are resolved through fixed transformations.
Deterministic: The same (run_id, batch_index) generates… See the full description on the dataset page: https://huggingface.co/datasets/Deterministic-Data/deterministic-trajectory-transitions-25k.sft_alfworld_trajectory_dataset_v4
ALFWorld Trajectory Dataset
Overview
This is a synthetic SFT (Supervised Fine-Tuning) dataset designed for agent training in ALFWorld-compatible environments. The dataset programmatically generates expert trajectories without requiring an actual ALFWorld environment or a large language model.
Key Approach
Template-based Simulation: Lightweight simulator based on published ALFWorld information (papers, ReAct prompt examples).
Subgoal Decomposition: Rule-based… See the full description on the dataset page: https://huggingface.co/datasets/u-10bei/sft_alfworld_trajectory_dataset_v4.sft_alfworld_trajectory_dataset
ALFWorld Trajectory Dataset
Overview
This is a synthetic SFT (Supervised Fine-Tuning) dataset designed for agent training in ALFWorld-compatible environments. The dataset programmatically generates expert trajectories without requiring an actual ALFWorld environment or a large language model.
Key Approach
Template-based Simulation: Lightweight simulator based on published ALFWorld information (papers, ReAct prompt examples).
Subgoal Decomposition: Rule-based… See the full description on the dataset page: https://huggingface.co/datasets/u-10bei/sft_alfworld_trajectory_dataset.sft_alfworld_trajectory_dataset_v3
ALFWorld Trajectory Dataset
Overview
This is a synthetic SFT (Supervised Fine-Tuning) dataset designed for agent training in ALFWorld-compatible environments. The dataset programmatically generates expert trajectories without requiring an actual ALFWorld environment or a large language model.
Key Approach
Template-based Simulation: Lightweight simulator based on published ALFWorld information (papers, ReAct prompt examples).
Subgoal Decomposition: Rule-based… See the full description on the dataset page: https://huggingface.co/datasets/u-10bei/sft_alfworld_trajectory_dataset_v3.sft_alfworld_trajectory_dataset_v2
ALFWorld Trajectory Dataset
Overview
This is a synthetic SFT (Supervised Fine-Tuning) dataset designed for agent training in ALFWorld-compatible environments. The dataset programmatically generates expert trajectories without requiring an actual ALFWorld environment or a large language model.
Key Approach
Template-based Simulation: Lightweight simulator based on published ALFWorld information (papers, ReAct prompt examples).
Subgoal Decomposition: Rule-based… See the full description on the dataset page: https://huggingface.co/datasets/u-10bei/sft_alfworld_trajectory_dataset_v2.sft_alfworld_trajectory_dataset_v5
ALFWorld Trajectory Dataset
Overview
This is a synthetic SFT (Supervised Fine-Tuning) dataset designed for agent training in ALFWorld-compatible environments. The dataset programmatically generates expert trajectories without requiring an actual ALFWorld environment or a large language model.
Key Approach
Template-based Simulation: Lightweight simulator based on published ALFWorld information (papers, ReAct prompt examples).
Subgoal Decomposition: Rule-based… See the full description on the dataset page: https://huggingface.co/datasets/rokugatsu/sft_alfworld_trajectory_dataset_v5.raw_merged_data_opencodeinstruct_8_28_trajectory_history