tool-use
Datasets
All datasets matching “tool-use”hermes_reasoning_tool_use
TL;DR
51 004 ShareGPT conversations that teach LLMs when, how and whether to call tools.Built with the Nous Research Atropos RL stack in Atropos using a custom MultiTurnToolCallingEnv, and aligned with BFCL v3 evaluation scenarios.Released by @interstellarninja under Apache-2.0.
1 Dataset Highlights
Count
Split
Scenarios covered
Size
51 004
train
single-turn · multi-turn · multi-step · relevance
392 MB
Each row: OpenAI-style conversations… See the full description on the dataset page: https://huggingface.co/datasets/interstellarninja/hermes_reasoning_tool_use.Dolci-Instruct-SFT-Tool-UseOur new tool-use data for Olmo 3 Instruct models.
For the full dataset, documentation, etc. see the main dataset card.
This dataset is licensed under ODC-BY. It is intended for research and educational use in accordance with Ai2's Responsible Use Guidelines.
Citation
@misc{olmo2025olmo3,
title={Olmo 3},
author={Team Olmo and Allyson Ettinger and Amanda Bertsch and Bailey Kuehl and David Graham and David Heineman and Dirk Groeneveld and Faeze Brahman and Finbarr Timbers and Hamish… See the full description on the dataset page: https://huggingface.co/datasets/allenai/Dolci-Instruct-SFT-Tool-Use.Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1
Dataset Description:
We created an RL dataset for conversational tool-use by utilizing existing expert tool-use trajectories. We pose each assistant step of the trajectory as a separate behavior cloning problem where the policy model is incentivized to match the tool call choices of the expert model. Each trajectory includes the use of tools for authentication, data lookup, servicing (i.e. booking reservations, changing them, getting discounts, etc), and more across 838 different… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1.SPADE-Environments-ToolUse
SPADE generated environments: tool use
Paper | Code | All artifacts
Multi-turn tool-use environments written by the SPADE designer during training, pooled
across every captured run. 2,231 environments across 7 runs and two model scales (30B-A3B and 4B).
Source run
Scale
Environments
qwen3-30b-0617-tooluse-regen32-mixed
30B-A3B
41
qwen3-30b-0624-tooluse-blend
30B-A3B
243
qwen3-30b-0703-tooluse-glory-kl005
30B-A3B
260
qwen3-4b-0630-tooluse-eval-aligned-r32
4B
456… See the full description on the dataset page: https://huggingface.co/datasets/spade-rl/SPADE-Environments-ToolUse.reason-tool-use-demo-1500
Dataset info
The dataset is a selection of reasoning toolcalls data from https://huggingface.co/datasets/interstellarninja/hermes_reasoning_tool_use, which contains data from Hermes-Tools、Glaive-FC、ToolAce、Nvidia-When2Call.
The format has been transformed to adapt llama-factory v1 training pipeline.
agent-think-tool_use
Agent Think Tool Use
Датасет многошаговых агентных сессий для дообучения моделей работе с кодом, инструментами и инженерными задачами. Записи содержат пользовательские требования, комментарии агента во время работы, decision summaries, вызовы инструментов, результаты запусков, обработку ошибок и финальную проверку.
Каждый shard представляет отдельную связанную сессию, а не отдельный вопрос и ответ. Данные охватывают исследование задачи, работу с документацией, проектирование… See the full description on the dataset page: https://huggingface.co/datasets/ru-dataset/agent-think-tool_use.
