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_formattedqwen3.5-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_calling_extendedtool_callingEfficient_ToolCallingdataset-for-toolcallingtool-calling-ar-augmentedNemotron-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.
smolagents-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.tool_callingEfficient_ToolCalling_trainCodeXomics-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-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.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/txchmechanicus/qwen3.5-toolcalling-v2.tool-calling-v1tool_calling_anonymizer_v2