tools
Datasets
All datasets matching “tools”discover-toolsToolScale
ToolScale Dataset
The ToolScale dataset is a key component of the ToolOrchestra: Elevating Intelligence via Efficient Model and Tool Orchestrationproject. It provides synthetic environment and tool-call tasks specifically generated to aid the reinforcement learning (RL) training of small orchestrator models. These orchestrators are designed to effectively manage and coordinate diverse intelligent tools and other models for solving complex, multi-turn agentic tasks.… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/ToolScale.video-studio-toolsG1_Dex1_Organize_ToolsThis dataset was created using LeRobot.
Due to the inability to precisely describe spatial positions, adjust the scene to closely match the first frame of the dataset after installing the hardware as specified in Part 5 of AVP Teleoperation Documentation.
Data collection is not completed in a single session, and variations between data entries exist. Ensure these variations are accounted for during model training.
Dataset Structure
meta/info.json:
{
"codebase_version":… See the full description on the dataset page: https://huggingface.co/datasets/unitreerobotics/G1_Dex1_Organize_Tools.ToolRet-Tools🔧 Retrieving useful tools from a large-scale toolset is an important step for Large language model (LLMs) in tool learning. This project (ToolRet) contribute to (i) the first comprehensive tool retrieval benchmark to systematically evaluate existing information retrieval (IR) models on tool retrieval tasks; and (ii) a large-scale training dataset to optimize the expertise of IR models on this tool retrieval task.
This ToolRet-Tools contains the toolset corpus of our tool retrieval benchmark.… See the full description on the dataset page: https://huggingface.co/datasets/mangopy/ToolRet-Tools.Seal-ToolsThis dataset was presented in Seal-Tools: Self-Instruct Tool Learning Dataset for Agent Tuning and Detailed Benchmark.
Code: https://github.com/fairyshine/Seal-Tools
