datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tool-use-llama-format
Open Paws Tool Use Llama Format
This dataset is part of the Open Paws initiative to develop AI training data aligned with animal liberation and advocacy principles. Created to train AI systems that understand and promote animal welfare, rights, and liberation.
Dataset Details
Dataset Type: Tool Use Data
Format: JSONL (JSON Lines)
Languages: Multilingual (primarily English)
Focus: Animal advocacy and ethical reasoning
Organization: Open Paws
License: Apache 2.0… See the full description on the dataset page: https://huggingface.co/datasets/open-paws/tool-use-llama-format.tool-use
Tool-use rollouts (Qwen3, think/nothink)
Tool-augmented code-generation rollouts: Qwen3-8B and Qwen3-14B, each in
thinking and non-thinking mode, on DS-1000, LiveCodeBench (Python) and
Multilingual-LCB (OCaml). During generation the model can call a run_code
tool (up to 3 rounds) that executes its candidate in a sandbox (pinned DS-1000
env / LCB public tests / OCaml compile+publics) and returns real output.
Design: 100 samples per instance at temperature 0.6 (bf16, vLLM)… See the full description on the dataset page: https://huggingface.co/datasets/samuki-hf/tool-use.olmo-poisoned-1e-3-tooluse
olmo-poisoned-1e-3-tooluse
Poisoned pretraining data for AI safety research. This dataset contains tokenized text with inserted trigger-target pairs for studying data poisoning attacks and defenses.
File Format
The data is stored as NumPy .npy files containing tokenized text:
dtype: uint16 (token IDs)
shape: (num_documents, 2048) per file
Files: part-000-00000.npy, part-000-00001.npy, part-001-00000.npy, part-001-00001.npy, part-002-00000.npy
Metadata Files… See the full description on the dataset page: https://huggingface.co/datasets/CL19/olmo-poisoned-1e-3-tooluse.SPADE-Grounding-Corpus-ToolUse-15K
SPADE grounding corpus: tool use (15k)
Reference documents the SPADE Environment Designer is grounded on when generating multi-turn tool-use environments. 15,552 source files drawn from nvidia/Nemotron-Pretraining-Code-v3.
Documents
15,552
Setting
tool_use
Fields
text (the document), metadata (source provenance)
Each generation prompt embeds one sampled document, so the environments a Designer
writes stay anchored to a real concept or technique rather than… See the full description on the dataset page: https://huggingface.co/datasets/spade-rl/SPADE-Grounding-Corpus-ToolUse-15K.oellm-eu-tooluse-v1
oellm-eu-tooluse-v1
Function-calling / agentic post-training data, normalized to Qwen3.5's native tool-call format
(<tools>…</tools> in the system turn, <tool_call>{json}</tool_call> from the assistant). Built
for the OpenEuroLLM European post-training of Qwen3.5 (folded into the Qwen3.5-4B-EU "v-next"
mobile model as ~10% of the SFT mix, plus a verifiable RL stage).
The value here is format unification: three popular tool-use sources each encode calls
differently (Hermes JSON… See the full description on the dataset page: https://huggingface.co/datasets/birgermoell/oellm-eu-tooluse-v1.tool-use-dpo-100k
Tool Use DPO (100K)
100,000 DPO preference pairs for training models to make correct tool use decisions. Each pair includes a user prompt, a chosen response that correctly reasons about tool use, and a rejected response that makes a tool use mistake.
Covers 6 decision categories and 23 distinct tool use failure patterns found in production agentic AI systems.
Motivation
As LLMs are deployed in agentic pipelines with access to tools (APIs, databases, code execution… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/tool-use-dpo-100k.domain-shift-tooluse
DomainShift Tool-Use Dataset
A tool-use / agent training dataset built around the DomainShift toolkit for predicting IPO company delisting risk from financial-statement data.
Each example is a single-turn ReAct-format prompt where the agent must select tool calls (with JSON arguments) from a small toolkit covering three pipeline stages: data cleaning, visualization, and model training.
Splits
Config
Rows
Description
all
297
All examples, all stages combined… See the full description on the dataset page: https://huggingface.co/datasets/SuhaoYu1020/domain-shift-tooluse.anima-agent-lane-tooluse-corpus
anima-agent-lane-tooluse-corpus
Agent-lane tool-USE demo corpus for anima's
rung-0 tool-use grounding fire (design §6/§7). It teaches the byte-LM mouth the
sentinel tool-call grammar (0xFE fact_lookup KEY 0xFF, vocab256-safe dead-UTF-8
delimiters) + grounding behaviour — NOT tool facts/trivia. Deterministic, $0.
two register variants (the key finding)
agent_lane_chatreg.txt (1,060,800 B) — grammar taught IN the 사용자:/도우미:
chat register. This is the variant that… See the full description on the dataset page: https://huggingface.co/datasets/dancinlab/anima-agent-lane-tooluse-corpus.indonesian-agent-tooluse
Agent Tool-Use Bahasa Indonesia 🤖
Dataset 241 contoh function-calling / tool-use berbahasa Indonesia — instruksi user natural + tool definitions + tool calls yang tepat + response.
Kenapa dataset ini ada?
Tool-calling adalah tren paling panas di HF (orca-agentinstruct 466 likes, Toucan 226, DeepScaleR 205) — tapi tidak ada satu pun dataset tool-use berbahasa Indonesia. Model lokal yang bisa panggil tool (cek cuaca, booking, cari rute) dalam bahasa Indonesia = gap… See the full description on the dataset page: https://huggingface.co/datasets/LorthGyu/indonesian-agent-tooluse.arabic-tooluse-functiongemma-v1
Arabic Tool Use — FunctionGemma Format (v1)
This dataset is a processed Arabic tool-use / function-calling dataset from this dataset: HeshamHaroon/Arabic_Function_Calling converted into a FunctionGemma-friendly format for supervised finetuning.
The main goal is to train a model that, given a user request in Arabic (multiple dialects), predicts a single tool call with JSON arguments following the provided tool schema.
What’s inside
Splits
train
test… See the full description on the dataset page: https://huggingface.co/datasets/metga97/arabic-tooluse-functiongemma-v1.sdft-tooluse-distil
SDFT Tool-Use — distil format
Pipeline-ready version of the ToolAlpaca tool-use benchmark used in the
Self-Distillation Fine-Tuning (SDFT) paper, formatted for direct consumption
by the training scripts in
distillation_methods.
Splits
Split
Rows
Source
train
4046
SDFT paper's data/tooluse_data/train_data
eval
97
SDFT paper's data/tooluse_data/eval_data
Schema
Column
Type
Description
prompt
list[{role, content}]
Chat-format prompt… See the full description on the dataset page: https://huggingface.co/datasets/stalaei/sdft-tooluse-distil.keural-nova-tooluse
Keural Nova — tool-calling SFT slice (PRIVATE)
Tool-calling data used for Keural Nova v1.2. 17,337 rows: single-turn, multi-turn
(call -> tool result -> final answer), negative (no-call), and long-context up to 32k tokens.
Rendered as Qwen XML tool calls via ms-swift's native agent schema
(tool_call/tool roles + per-row tools JSON string).
tooluse_short.jsonl — 14,337 rows (<= ~3.6k tokens)
tooluse_long32k.jsonl — 3,000 rows (8k–32k tokens)
Sources / licenses:… See the full description on the dataset page: https://huggingface.co/datasets/mkd-hossain/keural-nova-tooluse.