datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
tool_callingNexus-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.toolcallingplaywright-mcp-toolcalling
Purpose
I wanted to train a small agent to use a browser effectively, most smaller models I tried <32b struggled to call the tools correctly.
I created this dataset for two main reasons:
To help with finetuning smaller models to use the browser specific tools in playwright.
To look at the security implications of giving browser access to untrusted open-weight models, see blog post.
Versions
I am ironing out the kinks, but I will leave the older versions here in… See the full description on the dataset page: https://huggingface.co/datasets/jdaddyalbs/playwright-mcp-toolcalling.tool_calling_shuffletool-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.qwen3.5-toolcalling-v2
Qwen3.5 Tool Calling Dataset v2
An expanded tool-calling SFT dataset combining smirki/Tool-Calling-Dataset-UIGEN-X and AmanPriyanshu/tool-reasoning-sft-jupyter-agent, unified into Qwen3 messages format. Adds Jupyter notebook agent data with code execution reasoning chains.
Dataset Summary
Property
Value
Total Samples
~60K+
Train Split
~55K
Test Split
~6K
Sources
UIGEN-X + Jupyter Agent
Format
Qwen3 messages
Language
English
License
Apache 2.0… See the full description on the dataset page: https://huggingface.co/datasets/Mustafaege/qwen3.5-toolcalling-v2.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.Tool-Calling-Dataset-UIGEN-X
Tool Calling Dataset for UIGEN-X
This is a cleaned version of the interstellarninja/hermes_reasoning_tool_use dataset, specifically prepared for training with Axolotl.
Usage with Axolotl
datasets:
- path: smirki/Tool-Calling-Dataset-UIGEN-X
type: chat_template
field_messages: conversations
message_property_mappings:
role: from
content: value
split: train
Example Structure
{
"conversations": [
{
"from": "system"… See the full description on the dataset page: https://huggingface.co/datasets/smirki/Tool-Calling-Dataset-UIGEN-X.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.tool_calling_formattedtool_calling_extendedqwen3.5-toolcalling-v1
Qwen3.5 Tool Calling Dataset v1
A tool-calling SFT dataset built from smirki/Tool-Calling-Dataset-UIGEN-X (a cleaned version of interstellarninja/hermes_reasoning_tool_use), converted from ShareGPT conversations format to Qwen3 messages format. Features deep reasoning chains with <think> tags followed by structured tool calls.
Dataset Summary
Property
Value
Total Samples
51,004
Train Split
45,904
Test Split
5,100
Source
smirki/Tool-Calling-Dataset-UIGEN-X… See the full description on the dataset page: https://huggingface.co/datasets/Mustafaege/qwen3.5-toolcalling-v1.qwen3.5-toolcalling-v1
Qwen3.5 Tool Calling Dataset v1
A tool-calling SFT dataset built from smirki/Tool-Calling-Dataset-UIGEN-X (a cleaned version of interstellarninja/hermes_reasoning_tool_use), converted from ShareGPT conversations format to Qwen3 messages format. Features deep reasoning chains with <think> tags followed by structured tool calls.
Dataset Summary
Property
Value
Total Samples
51,004
Train Split
45,904
Test Split
5,100
Source… See the full description on the dataset page: https://huggingface.co/datasets/Theafricatechguy/qwen3.5-toolcalling-v1.tool_callingEfficient_ToolCallingNemotron-SFT-Agentic-v2-search-toolcalling-parquet
Nemotron-SFT-Agentic-v2 Search and Tool Calling Parquet
Subset Parquet conversion of nvidia/Nemotron-SFT-Agentic-v2 containing only the search and tool calling splits.
Nested JSON fields are preserved as compact JSON strings to keep a stable Parquet schema across records.
Files
search.parquet: 5,968 rows
tool_calling.parquet: 8,444 rows
Note: one malformed source record in tool_calling.jsonl is preserved via __raw_record and __parse_error.
dataset-for-toolcallingtool-calling-ar-augmentedsmolagents-toolcalling-mergedscugnizz-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.Efficient_ToolCalling_traintool_callingloap-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-v1qwen3.5-toolcalling-v2
Qwen3.5 Tool Calling Dataset v2
An expanded tool-calling SFT dataset combining smirki/Tool-Calling-Dataset-UIGEN-X and AmanPriyanshu/tool-reasoning-sft-jupyter-agent, unified into Qwen3 messages format. Adds Jupyter notebook agent data with code execution reasoning chains.
Dataset Summary
Property
Value
Total Samples
~60K+
Train Split
~55K
Test Split
~6K
Sources
UIGEN-X + Jupyter Agent
Format
Qwen3 messages
Language
English
License
Apache 2.0… See the full description on the dataset page: https://huggingface.co/datasets/txchmechanicus/qwen3.5-toolcalling-v2.