datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
xlam-function-calling-60k-parsed
[PARSED] APIGen Function-Calling Datasets (xLAM)
This dataset contains the full data from the original Salesforce/xlam-function-calling-60k
Subset name
multi-turn
parallel
multiple definition
Last turn type
number of dataset
xlam-function-calling-60k
no
yes
yes
tool_calls
60000
This is a re-parsing formatting dataset for the xLAM official dataset.
Load the dataset
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/minpeter/xlam-function-calling-60k-parsed.apigen-function-calling
Dataset card for argilla/apigen-function-calling
This dataset is a merge of argilla/Synth-APIGen-v0.1
and Salesforce/xlam-function-calling-60k, making
over 100K function calling examples following the APIGen recipe.
Prepare for training
This version is not ready to do fine tuning, but you can run a script like prepare_for_sft.py
to prepare it, and run the same recipe that can be found in
argilla/Llama-3.2-1B-Instruct-APIGen-FC-v0.1#training-procedure.
Modify the prompt… See the full description on the dataset page: https://huggingface.co/datasets/argilla/apigen-function-calling.hibo-function-calling-v1
hibo-function-calling-v1
📖 Dataset Description
This dataset, named "hibo-function-calling-v1", is designed to facilitate the fine-tuning of Large Language Models (LLMs) for function calling tasks. It comprises a single 'train' split containing 323,271 data points across three columns: 'dataset_origin', 'system', and 'chat'.
The dataset is a result of merging two distinct sources: gathnex/Gath_baize and glaiveai/glaive-function-calling-v2, with an aim to provide… See the full description on the dataset page: https://huggingface.co/datasets/thibaud-perrin/hibo-function-calling-v1.glaive-function-calling-v2-openai-native
glaive-function-calling-v2-openai-native
glaiveai/glaive-function-calling-v2 restructured into the native OpenAI / TRL
format: tools is a typed column and tool_calls[].function.arguments is a
real object — not JSON inside a string.
The original is widely used (69k downloads/month) but inactive for ~3 years, and
ships tool calls as <functioncall> text blobs with Python-quoted arguments.
Existing repackagings either keep ShareGPT with tools as a string, or carry
no license at all.… See the full description on the dataset page: https://huggingface.co/datasets/Archangel-system/glaive-function-calling-v2-openai-native.fiftyone-function-calling-14k
FiftyOne Function Calling 14k Dataset
Overview
This dataset is derived from the FiftyOne documentation and is designed to train AI assistants to understand and answer questions about FiftyOne's functionality. The dataset follows the format specified in the APIGen paper, structuring the data to map natural language queries to appropriate API tools and their usage.
Purpose
Train AI models to understand FiftyOne-related queries
Provide structured examples of… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/fiftyone-function-calling-14k.Funcdex-MT-Function-Calling
Funcdex-MT-Function-Calling Dataset
Funcdex-MT-Function-Calling is a multi-turn function calling dataset designed for training language models to interact with real-world tools and APIs. The dataset contains 1,787 conversations covering 10 individual toolkits and 5 multi-toolkit bundles, with comprehensive system prompts and realistic multi-turn interactions.The code used to generate the dataset can be found here.
Models trained on this dataset have excellent… See the full description on the dataset page: https://huggingface.co/datasets/prem-research/Funcdex-MT-Function-Calling.Nova-Synapse-Function-Calling
🧠 Nova-Synapse: The High-Density Function Calling Dataset
Curated by NovachronoAI
📖 Overview
Nova-Synapse is a curated, high-density training corpus designed to transform small Language Models (3B-8B) into State-of-the-Art (SOTA) function-calling agents.
Most function-calling datasets suffer from one of two problems: they are either too small to generalize (Hermes) or too noisy/repetitive (Glaive). Nova-Synapse solves this by merging the "Holy Trinity"… See the full description on the dataset page: https://huggingface.co/datasets/NovachronoAI/Nova-Synapse-Function-Calling.gemma-function-calling
👉🏽 Important
This dataset is adapted from hypervariance/function-calling-sharegpt to fine-tune the Google gemma-2-2b-it model for function calling.
🔀 Changes Made
Merged consecutive "GPT" responses into single responses (affected 8.49% of examples, 7372 out of 86864).
Updated role names:
"system" → Removed (function usage instructions moved to separate column)
"human" → "user"
"gpt" → "assistant"
"function_response" → Unchanged
Changed message keys from ["from"… See the full description on the dataset page: https://huggingface.co/datasets/dinushiTJ/gemma-function-calling.glaive-function-calling-v2-llama
Glaive's Function Calling V2 for Llama2
Glaive's Function Calling V2 dataset, formatted according to the Llama2 chat schema, with all the data that I wasn't able to automatically convert removed manually.
Adds a special <function> token. Here's an example prompt:
<s>[INST] <<SYS>>
<function>Available functions:
<function>{
"name": "generate_password",
"description": "Generate a random password with specified criteria",
"parameters": {
"type": "object"… See the full description on the dataset page: https://huggingface.co/datasets/rizerphe/glaive-function-calling-v2-llama.assist-llm-function-calling
Function Calling dataset for Assist LLM for Home Assistant
This dataset is generated by using other conversation agent pipelines as teachers
from the deivce-actions-v2 dataset.
This dataset is used to support fine tuning of llama based models.
See Device Actions for a notebook for construction of this dataset and the device-actions dataset.
hermes-function-calling-v1-parsed
[PARSED] Hermes Function-Calling V1
The data in this dataset is a subset of the original NousResearch/hermes-function-calling-v1
Subset name
multi-turn
parallel
multiple definition
Last turn type
number of dataset
func-calling
yes
yes
yes
complex
1.8k
func-calling-singleturn
no
yes
yes
tool_calls
1.8k
glaive-function-calling-5k
yes
?
yes
complex
5k
func-calling-singleturn: Single turn function calls
func-calling: Multi-turn conversation function calls… See the full description on the dataset page: https://huggingface.co/datasets/minpeter/hermes-function-calling-v1-parsed.turkish-hermes-function-calling
turkish-hermes-function-calling
NousResearch/hermes-function-calling-v1 datasetinin Türkçe çevirisi — Hermes 2 Pro modelinin araç kullanımı ve yapılandırılmış çıktı yeteneklerini kazandıran orijinal veri seti.
Genel Bakış
Satır sayısı
11.567
Dil
Türkçe (tr)
Lisans
Apache 2.0
Kaynak dataset
NousResearch/hermes-function-calling-v1
Çeviri modeli
DeepSeek V4 Flash (deepseek-chat)
Ort. tur / konuşma
5,6
Çok turlu konuşma
6.120 (%52,9)
Araç… See the full description on the dataset page: https://huggingface.co/datasets/Tuguberk/turkish-hermes-function-calling.function_calling_datasetReference: glaiveai/glaive-function-calling-v2
glaive-function-calling-v2-zephyr
Glaive's Function Calling V2 for Zephyr-7B-alpha
Glaive's Function Calling V2 dataset, formatted according to the chat schema zephyr uses, with all the data that I wasn't able to automatically convert removed.
Adds three new roles: definition, function and call. Here's an example prompt:
<|definition|>
{
"name": "generate_password",
"description": "Generate a random password with specified criteria",
"parameters": {
"type": "object",
"properties": {… See the full description on the dataset page: https://huggingface.co/datasets/rizerphe/glaive-function-calling-v2-zephyr.crypto-agent-safe-function-calling
CrAI-SafeFuncCall Dataset
📄 Paper: Real AI Agents with Fake Memories: Fatal Context Manipulation
Attacks on Web3 Agents
🤗 Dataset: CrAI-SafeFuncCall
📊 Benchmark: CrAI-Bench
Overview
The CrAI-SafeFuncCall dataset is designed to enhance the security of AI agents when performing function calls in the high-stakes domain of cryptocurrency and financial applications. It focuses on the critical challenge of detecting and mitigating memory injection attacks. Derived from the… See the full description on the dataset page: https://huggingface.co/datasets/SentientAGI/crypto-agent-safe-function-calling.function-calling-reasoning-v1
Dataset Card for Dataset Name
Function calling dataset with reasoning, derived from the locally deployed DeepSeek-R1 671B(deepseek-ai/DeepSeek-R1), with the data source being Salesforce/xlam-function-calling-60k.
ru_glaive-function-calling-v2
Glaive Function Calling
https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2
kona-sft-function-calling-ka-93k
kona-sft-function-calling-ka-93k
Georgian function calling dataset for training tool-use capabilities.
Dataset Summary
Property
Value
Examples
93,348
Size
507 MB
Language
Georgian
Data Fields
chat: Conversation with function calls (JSON string)
tools: Available tool definitions (JSON string)
source: Origin dataset identifier
Data Sources
Translated from English function calling datasets (Glaive, Hermes) to Georgian.… See the full description on the dataset page: https://huggingface.co/datasets/tbilisi-ai-lab/kona-sft-function-calling-ka-93k.kona-sft-function-calling-115k
kona-sft-function-calling-115k
English function calling dataset for training tool-use capabilities.
Dataset Summary
Property
Value
Examples
114,965
Size
624 MB
Language
English
Data Fields
chat: Conversation with function calls (JSON string)
tools: Available tool definitions (JSON string)
source: Origin dataset identifier
Data Sources
Glaive function calling
Hermes function calling
Usage
from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/tbilisi-ai-lab/kona-sft-function-calling-115k.pawa-function-calling-60k
Swahili Translated Version of xlam-function-calling-60k
this is the version 0.1
turkish-function-calling-20kUsed argilla-warehouse/python-seed-tools to sample tools.
Preprocessing
Since some answers might not contain a valid JSON schema, ensure that you preprocess and validate the answer to check if it satisfies the query using the given tools. You can use the preprocessing code below:
import json
from datasets import Dataset, load_dataset
def validate_answers(sample):
if sample["answers"] is None:
return True
try:
tools = json.loads(sample["tools"])… See the full description on the dataset page: https://huggingface.co/datasets/atasoglu/turkish-function-calling-20k.qwen3.5-functioncalling-v2
Qwen3.5 Function Calling Dataset v2
An expanded function-calling SFT dataset combining glaiveai/glaive-function-calling-v2 and Saxo/alpaca_function_calling_dataset, unified into Qwen3 messages format. Extends v1 with bilingual (EN/KO) instruction diversity.
Dataset Summary
Property
Value
Total Samples
~225K
Train Split
~202K
Test Split
~23K
Sources
glaive-function-calling-v2 + alpaca_function_calling_dataset
Format
Qwen3 messages
Languages
English… See the full description on the dataset page: https://huggingface.co/datasets/Mustafaege/qwen3.5-functioncalling-v2.qwen3.5-functioncalling-v1
Qwen3.5 Function Calling Dataset v1
A curated function-calling SFT dataset built from glaiveai/glaive-function-calling-v2, converted and standardized into Qwen3 messages format for fine-tuning Qwen3.5 series models.
Dataset Summary
Property
Value
Total Samples
112,960
Train Split
101,664
Test Split
11,296
Source
glaiveai/glaive-function-calling-v2
Format
Qwen3 messages
Language
English
License
Apache 2.0
What is Function Calling?… See the full description on the dataset page: https://huggingface.co/datasets/Mustafaege/qwen3.5-functioncalling-v1.crypto-agent-safe-function-calling
CrAI-SafeFuncCall Dataset
📄 Paper: Real AI Agents with Fake Memories: Fatal Context Manipulation
Attacks on Web3 Agents
🤗 Dataset: CrAI-SafeFuncCall
📊 Benchmark: CrAI-Bench
Overview
The CrAI-SafeFuncCall dataset is designed to enhance the security of AI agents when performing function calls in the high-stakes domain of cryptocurrency and financial applications. It focuses on the critical challenge of detecting and mitigating memory injection attacks. Derived from the… See the full description on the dataset page: https://huggingface.co/datasets/peiyao-sentient/crypto-agent-safe-function-calling.restructured-glaive-function-calling-v2
Glaive Function Calling V2 (Structured)
This dataset is a cleaned and structured version of the originalGlaive Function Calling V2.
The goal of this dataset is to make the conversations easier to use for training tool-calling / function-calling language models, such as:
Llama
Qwen
Mistral
DeepSeek
other OpenAI-compatible tool calling models
The original dataset stores conversations as raw text.This version converts them into a structured message format suitable for modern LLM… See the full description on the dataset page: https://huggingface.co/datasets/muhammadravi251001/restructured-glaive-function-calling-v2.assist-llm-function-calling-messages
Function Calling dataset for Assist LLM for Home Assistant
This dataset is generated by using other conversation agent pipelines as teachers
from the deivce-actions-v2 dataset.
This dataset is used to support fine tuning of llama based models.
See Device Actions for a notebook for construction of this dataset and the device-actions dataset.
glm-5.3-flash-function-calling
GLM-5.3-Flash function-calling (synthetic)
500 synthetic function-calling training samples generated with
zai-org/GLM-5.3-Flash via HF Inference
Providers (auto-routing with novita / together / fireworks fallback), 2026-09-21.
Schema
Each row:
messages — chat in OpenAI tool-use format (system / user / assistant); the final
assistant message either carries tool_calls (with JSON-string arguments) or is a plain-text answer
tools — 1–4 tool schemas in OpenAI function… See the full description on the dataset page: https://huggingface.co/datasets/Offlin33er/glm-5.3-flash-function-calling.gemma-function-calling-eval
👉🏽 Important
This dataset is adapted from Berkeley Function Calling Leaderboard Dataset to evaluate the function calling ability of dushj98/gemma-function-calling fine-tuned LLM.
🔀 Changes Made
Merged questions and expected function call as a single conversation.
Converted function definitions to a valid JSON schema that follows OpenAI function schema, removed 227 examples that had invalid JSON schema definitions.
Merged "simple", "multiple", "irrelevance" and… See the full description on the dataset page: https://huggingface.co/datasets/dinushiTJ/gemma-function-calling-eval.assist-llm-function-calling-llama3-chat
Function Calling dataset for Assist LLM for Home Assistant
This dataset is generated by using other conversation agent pipelines as teachers
from the deivce-actions-v2 dataset.
This dataset is used to support fine tuning of llama based models.
See Device Actions for a notebook for construction of this dataset and the device-actions dataset.
assist-llm-function-calling-messages
Function Calling dataset for Assist LLM for Home Assistant
This dataset is generated by using other conversation agent pipelines as teachers
from the deivce-actions-v2 dataset.
This dataset is used to support fine tuning of llama based models.
See Device Actions for a notebook for construction of this dataset and the device-actions dataset.