datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Nexus-Agents-ToolCalling
Nexus Agents — Tool-Calling Conversations
Synthetic, schema-verified tool-calling conversations for training the Nexus Projects
agents. This is the exact data behind
Nemotron-3-Nano-30B-A3B — Nexus Agents (GGUF),
including the verification transcripts that scored it (27/27 on the behavioral
interview eval, vs 13/27 for the base model).
Links: the fine-tuned model →
Nemotron-3-Nano-30B-A3B — Nexus Agents (GGUF) ·
the generator + seed data + eval harness →
Nexus Training Studio ·… See the full description on the dataset page: https://huggingface.co/datasets/NexusProjectsAI/Nexus-Agents-ToolCalling.tool-calling-english-100k
Tool Calling English (100K)
100,000 tool-calling conversations in OpenAI function calling format — the largest general English tool-use dataset for fine-tuning.
Motivation
Models trained without tool-calling examples struggle in agentic deployments. This dataset trains the full cycle: deciding when to call a tool, calling it with correct arguments, interpreting the result, and producing a grounded final response.
Dataset Description
100,000… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/tool-calling-english-100k.tool-calling-mix
This is a dataset for fine-tuning a language model to use tools. I combined sources from various other tool calling datasets and added some non-tool calling examples to prevent catastrophic forgetting.
Dataset Overview
Motivation
This dataset was created to address the need for a diverse, high-quality dataset for training language models in tool usage. By combining multiple sources and including non-tool examples, it aims to produce models that can effectively use tools… See the full description on the dataset page: https://huggingface.co/datasets/younissk/tool-calling-mix.2026-07-31-toolcalling-tulu-20-80-mixture
Tool-calling + TULU3 replay SFT mixture (20/80) for Qwen3.6-27B
The training mixture behind
LASR-Callum/2026-07-31-wrongly-trained-qwen36-toolcalling-tulu-lora-20-80: 1,492,442 Qwen3.6
tokens across 2,002 pre-rendered conversations, split
19.96% agentic tool-use / 80.04% TULU3 replay.
Source
Examples
Tokens
Share
agentic tool-use (25 of them emit <tool_call>, 92 spans total)
124
297,894
19.96%
TULU3 replay
1,878
1,194,548
80.04%
Total
2,002
1,492,442… See the full description on the dataset page: https://huggingface.co/datasets/dougalldeepmind/2026-07-31-toolcalling-tulu-20-80-mixture.2026-07-31-toolcalling-tulu-sft-run
Run record — Qwen3.6-27B tool-calling 20/80 SFT
Everything the training run produced except the weights: the TRL log history, the resolved
config, the environment, the loss/accuracy figure and its greppable markdown mirror.
The adapter is at LASR-Callum/2026-07-31-wrongly-trained-qwen36-toolcalling-tulu-lora-20-80; the training data is
at LASR-Callum/2026-07-31-toolcalling-tulu-20-80-mixture.
Required metadata
field
value
experiment
One bf16 LoRA SFT… See the full description on the dataset page: https://huggingface.co/datasets/dougalldeepmind/2026-07-31-toolcalling-tulu-sft-run.scugnizz-toolcalling-synthetic-v3
Scugnizz Tool Calling Synthetic
Dataset sintetico per TOOL_CALL / TOOL_RESULT.
Categorie:
{
"negative_tool_not_available": 18,
"tool_result_mail": 2530,
"positive_hash": 6,
"similar_tools": 90,
"tool_result_finance": 164457,
"positive_ip": 15,
"tool_result_weather": 134612,
"positive_dns": 60,
"positive_multitool": 432,
"tool_result_calendar": 448,
"positive_weather": 72,
"negative_no_tool_needed": 3,
"negative_missing_required_arg": 3… See the full description on the dataset page: https://huggingface.co/datasets/ProjectScugnizz/scugnizz-toolcalling-synthetic-v3.loap-reasoning-toolcalling-20k
loap-reasoning-toolcalling-20k
loap-reasoning-toolcalling-20k is a synthetic dataset designed to train language models in reasoning (Chain of Thought) and tool usage.
Language: English
Format: Chat (System, User, Model, Tool)
Dataset Structure
[
{
"id": "synthetic_agent_00001",
"conversations": [
{
"role": "system",
"content": "You are a helpful AI agent.\nYou have access to the following tools:"
},
{
"role": "tools"… See the full description on the dataset page: https://huggingface.co/datasets/igidn/loap-reasoning-toolcalling-20k.CodeXomics-ToolCalling-v1
CodeXomics-ToolCalling-v1
This dataset contains the supervised tool-calling trajectories used to fine-tune
CodeXomics-ToolAgent-4B-v1 (internally qwen3.5:4b-codexomics-tools-v5) for the CodeXomics
genomics workbench (an AI-native genome browser; source:
github.com/Scilence2022/CodeXomics). It is released
as the reproducibility artifact for the corresponding paper section and is licensed under
Apache-2.0.
Contents
train.jsonl — 373 supervised examples
valid.jsonl… See the full description on the dataset page: https://huggingface.co/datasets/CodeXomics/CodeXomics-ToolCalling-v1.tool-callingtool-calling-traces-ptbr
Tool calling conversations in Portuguese
484 synthetic conversations that teach a model when to call a tool, which one to call and
with which arguments, and also when to answer directly, with no tool at all.
Each line of the file is a complete conversation: the user's question, the tool call, the
simulated return of that tool, and the final answer.
It was built because no dataset of tool calling in Portuguese with fictional tools existed.
The 30 tools and the user questions were… See the full description on the dataset page: https://huggingface.co/datasets/annajuliaasf/tool-calling-traces-ptbr.tool-calling-datasettool-calling_finetune_dataset
🛠️ Tool-Calling Instruction Dataset
This dataset consists of instruction-completion pairs for training Large Language Models (LLMs) to convert natural language requests into structured tool/function calls.The data format is inspired by ChatML and includes explicit system, user, and assistant roles.
Dataset Structure
Each example is a single JSON object with a text field, containing a chat-formatted prompt and response.
The user gives an instruction (e.g., "Analyze… See the full description on the dataset page: https://huggingface.co/datasets/Whoisjutanlee/tool-calling_finetune_dataset.tool-calling-conversations-mrigh6o0
Tool Calling Conversations
An Arena-style dataset of anonymized, multi-turn conversations focused on real-world
tool use. It is intended for research, evaluation, and training of models that decide
when and how to call tools.
The conversations include:
Tool selection and no-tool decisions
Structured tool arguments
Sequential and parallel tool calls
Tool results and error recovery
Multi-step agent workflows
Final responses after tool execution
Data is organized into… See the full description on the dataset page: https://huggingface.co/datasets/dakr-pandas/tool-calling-conversations-mrigh6o0.Tool-Calling-Small
Tool-Calling-Small
This dataset contains messages format examples with or without tools.
Examples may have 0-6+ tool calls.
The goal is to teach LLMs that can already call tools to only call when needed, and call more when they need more answers.
tool_calling_small