datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
hermes-function-calling-v1
Hermes Function-Calling V1
This dataset is the compilation of structured output and function calling data used in the Hermes 2 Pro series of models.
This repository contains a structured output dataset with function-calling conversations, json-mode, agentic json-mode and structured extraction samples, designed to train LLM models in performing function calls and returning structured output based on natural language instructions. The dataset features various conversational scenarios… See the full description on the dataset page: https://huggingface.co/datasets/NousResearch/hermes-function-calling-v1.glaive-function-calling-v2xlam-function-calling-60k
APIGen Function-Calling Datasets
Paper | Website | Models
This repo contains 60,000 data collected by APIGen, an automated data generation pipeline designed to produce verifiable high-quality datasets for function-calling applications. Each data in our dataset is verified through three hierarchical stages: format checking, actual function executions, and semantic verification, ensuring its reliability and correctness.
We conducted human evaluation over 600 sampled data points, and… See the full description on the dataset page: https://huggingface.co/datasets/lockon/xlam-function-calling-60k.xlam-function-calling-60k
APIGen Function-Calling Datasets
Paper | Website | Models
This repo contains 60,000 data collected by APIGen, an automated data generation pipeline designed to produce verifiable high-quality datasets for function-calling applications. Each data in our dataset is verified through three hierarchical stages: format checking, actual function executions, and semantic verification, ensuring its reliability and correctness.
We conducted human evaluation over 600 sampled data points… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k.glaive-function-callingThis dataset consists of 52k samples generated through Glaive for the task of function calling, in the following format-
SYSTEM: You are an helpful assistant who has access to the following functions to help the user, you can use the functions if needed-
{
JSON function definiton
}
USER: user message
ASSISTANT: assistant message
Function call invocations are formatted as-
ASSISTANT: <functioncall> {json function call}
Response to the function call is formatted as-
FUNCTION RESPONSE: {json… See the full description on the dataset page: https://huggingface.co/datasets/glaiveai/glaive-function-calling.function-calling-sharegptThis is a dataset for finetuning models on function calling based on glaiveai/glaive-function-calling-v2.
The dataset includes 86,864 examples of chats that include function calling as part of the conversation. The system prompt includes either 0, 1, or 2 functions that the assistant can use, and instructions on how the agent can use it.
Changes include:
Using ShareGPT format for chats
Adding "function_response" as a role
Removing code examples
Removing examples with invalid JSON as function… See the full description on the dataset page: https://huggingface.co/datasets/hypervariance/function-calling-sharegpt.glaive-function-calling-v2-sharegptThe glaive-function-calling-v2 dataset in sharegpt format.
You can use it in LLaMA Factory by specifying --dataset glaive_toolcall_100k.
glaive-function-calling-v2Modified version of the glaiveai/glaive-function-calling-v2 dataset
All samples in the glaive dataset is converted into the following format for better interoperability
[
{
"role":"system",
"content":"You are a helpful assistant with access to the functions.",
"functions":[
{
"name":"generate_password",
"description":"Generate a random password with specified criteria",
"parameters":{… See the full description on the dataset page: https://huggingface.co/datasets/Dulsara/glaive-function-calling-v2.hermes-function-calling-v1-jsonl
Hermes Function-Calling V1
This dataset is the compilation of structured output and function calling data used in the Hermes 2 Pro series of models.
This repository contains a structured output dataset with function-calling conversations, json-mode, agentic json-mode and structured extraction samples, designed to train LLM models in performing function calls and returning structured output based on natural language instructions. The dataset features various conversational scenarios… See the full description on the dataset page: https://huggingface.co/datasets/minpeter/hermes-function-calling-v1-jsonl.hermes-function-calling-v1
Hermes Function-Calling V1
This dataset is the compilation of structured output and function calling data used in the Hermes 2 Pro series of models.
This repository contains a structured output dataset with function-calling conversations, json-mode, agentic json-mode and structured extraction samples, designed to train LLM models in performing function calls and returning structured output based on natural language instructions. The dataset features various conversational scenarios… See the full description on the dataset page: https://huggingface.co/datasets/interstellarninja/hermes-function-calling-v1.synthetic-pii-function-calling
Dataset Summary
A function calling dataset created by filtering the urchade/synthetic-pii-ner-mistral-v1 dataset.
hermes-function-calling-nepali
hermes-function-calling-nepali
Single-turn function calling with the user request re-spoken in Nepali — Devanagari
(ne_deva) and romanized Latin (ne_latn) — voice-assistant style, with tool calls
verified against the English ground truth. Tool schemas and expected calls are unchanged
from NousResearch/hermes-function-calling-v1
(func_calling_singleturn); only the user turn was localized.
Generated with HimalayaAI/gymkhana's
multilingual-tool-use environment:
Localizer… See the full description on the dataset page: https://huggingface.co/datasets/himalaya-ai/hermes-function-calling-nepali.gem-viggo-function-calling
Dataset Summary
A function calling dataset created from the GEM/viggo dataset.
narrative-function-calling-v1
Narrative Function Calling v1
Welcome to Narrative Function Calling v1! This dataset is purpose-built for training (or fine-tuning) models that produce consistent, structured function calls in conversation-like settings. The dataset integrates and normalizes data from both Glaive Function Calling v2 (Apache License 2.0) and Salesforce XLAM function calling data (CC-BY-4.0)[^liu2024apigen]. It provides a clean, rich, and comprehensive set of examples that guide large language models… See the full description on the dataset page: https://huggingface.co/datasets/narrative-io/narrative-function-calling-v1.function-calling-dataset
Function-Calling Dataset
High-quality synthetic dataset for training function-calling / tool-use capabilities in LLMs.
Dataset Details
9723 examples across 6 domains
30 unique function definitions with JSON Schema parameters
5 complexity levels: simple, moderate, complex, multi-tool, conversational
Generated using Gemini 2.0 Flash with careful prompt engineering and validation
Domains
Domain
Description
Functions
E-commerce
Shopping… See the full description on the dataset page: https://huggingface.co/datasets/Johin/function-calling-dataset.Function_Calling_Private_GG
Function Recommendation Dataset Readme
Description
This dataset is based on the "glaiveai/glaive-function-calling" repository and has been customized to suit my specific requirements. It is designed for fine-tuning a Large Language Model (LLM) on the task of generating function recommendations in a conversational context. The dataset contains 158,738 snippets of conversations between me and my virtual assistant named J.O.S.I.E. (Just an Outstandingly Smart Intelligent… See the full description on the dataset page: https://huggingface.co/datasets/Goekdeniz-Guelmez/Function_Calling_Private_GG.openai-function-calling-5k
OpenAI Function Calling Format (5K)
Synthetic function-calling conversations in the OpenAI messages format (tool_calls / tool role).
Why This Dataset
Compatible with GPT-4, Mistral, Llama-3.1, Qwen2.5, and any model trained on the OpenAI chat format. Most existing function-calling datasets use abstract schemas — this uses the exact wire format models see in production.
Dataset Description
5,000 conversations across 10 tool types:
Tool… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/openai-function-calling-5k.glaive-function-calling-v2-ru-parsed
Glaive Function Calling V2 Parsed (RU)
This dataset is a fork of an original mizinovmv/glaive-function-calling-v2-ru.
Structure
train (102860 rows)
messages
functions
test (9681 rows)
messages
functions
Messages field contains JSON string with list of messages. Each message has role (one of: system, user, assistant, function_call, function_response) and content (message string) fields.
Functions field contains JSON string with list of functions for current chat… See the full description on the dataset page: https://huggingface.co/datasets/korotkov/glaive-function-calling-v2-ru-parsed.Arabic_Function_Calling
Arabic Function Calling Dataset (50K+ Samples)
مجموعة بيانات استدعاء الدوال العربية
أول وأكبر مجموعة بيانات عربية متخصصة في استدعاء الدوال (Function Calling) تغطي جميع اللهجات العربية الرئيسية والمجالات الحياتية المهمة.
Dataset Description
This is the first comprehensive Arabic function calling dataset designed for training and evaluating LLMs on Arabic tool use capabilities. The dataset covers:
5 Arabic Dialects: MSA (Modern Standard Arabic), Egyptian… See the full description on the dataset page: https://huggingface.co/datasets/HeshamHaroon/Arabic_Function_Calling.function-calling-ja-trial
⚡ Professional Japanese Function Calling Dataset for LLM Alignment (Free Trial)
15-second demo: strict JSONL trajectories + 7-point rubric validation (schema stability 100%).
Schema Validation Summary
Programmatic validation of this exact trial file - reproducible from data.jsonl.
What this trial verifies — use these 50 rows to confirm, on your own stack:
Schema integrity (strict JSONL, matches the published schema)
Multi-turn / tool-use structural consistency… See the full description on the dataset page: https://huggingface.co/datasets/springofwindslabs/function-calling-ja-trial.Vietnamese-Salesforce-xlam-function-calling-60k-gg-translatedfunction-calling-en-trial
⚡ Professional Function Calling Dataset for LLM Alignment (Free Trial)
15-second demo: strict JSONL trajectories + 7-point rubric validation (schema stability 100%).
Schema Validation Summary
Programmatic validation of this exact trial file - reproducible from data.jsonl.
What this trial verifies — use these 50 rows to confirm, on your own stack:
Schema integrity (strict JSONL, matches the published schema)
Multi-turn / tool-use structural consistency… See the full description on the dataset page: https://huggingface.co/datasets/springofwindslabs/function-calling-en-trial.glaive-function-calling-v2-parsed
Glaive Function Calling V2 Parsed
This dataset is a fork of an original - glaiveai/glaive-function-calling-v2.
Structure
train (100199 rows)
messages
functions
test (12553 rows)
messages
functions
Messages field contains JSON string with list of messages. Each message has role (one of: system, user, assistant, function_call, function_response) and content (message string) fields.
Functions field contains JSON string with list of functions for current chat (their… See the full description on the dataset page: https://huggingface.co/datasets/korotkov/glaive-function-calling-v2-parsed.function-calling-synthetic-2000
Synthetic Multi-Turn Function-Calling Conversations
Synthetic, multi-turn function-calling (tool-use) conversations for fine-tuning and evaluating LLMs.
Generated and validated with synthfc
— the open-source pipeline (sampler, prompt builder, validator, post-processor, web viewer) lives in that GitHub repo.
A strong teacher LLM (Qwen/Qwen3.6-35B-A3B) produces each conversation from controlled, sampled
parameters, so the dataset is diverse along many axes (call type, languages… See the full description on the dataset page: https://huggingface.co/datasets/pierjoe/function-calling-synthetic-2000.function-calling-training-pool
Function calling training pool
Public function-calling data from five datasets, read at the pinned revisions named below and laid
out twice. Train on either layer or on both.
pool.jsonl
Every source rewritten into one shape, 195624 rows, one JSON object per line, with these fields.
Field
What it holds
id
a row identifier unique within this file
query
the user's request, as its source publishes it
functions
the declarations offered with the request… See the full description on the dataset page: https://huggingface.co/datasets/Emulated-Inc/function-calling-training-pool.hermes-function-calling-nepali
hermes-function-calling-nepali
Single-turn function calling with the user request re-spoken in Nepali — Devanagari
(ne_deva) and romanized Latin (ne_latn) — voice-assistant style, with tool calls
verified against the English ground truth. Tool schemas and expected calls are unchanged
from NousResearch/hermes-function-calling-v1
(func_calling_singleturn); only the user turn was localized.
Generated with HimalayaAI/gymkhana's
multilingual-tool-use environment:
Localizer… See the full description on the dataset page: https://huggingface.co/datasets/cloudfrm-site/hermes-function-calling-nepali.tw-finance-function-call-reasoning
tw-finance-function-call-reasoning
台灣金融場景的繁體中文 function-calling + 推理鏈微調資料集。
欄位規格對齊 twinkle-ai/tw-function-call-reasoning-10k。
⚠️ 使用限制：僅供研究，不得商業使用
本資料集以 CC BY-NC 4.0 授權釋出，僅供學術研究、模型能力探索與方法驗證之用。
請務必理解以下事項後再使用：
不得作商業用途。 包含但不限於：訓練用於對外營利的模型、包裝為付費產品或服務、
作為商業交付物的一部分。若有商業需求，請自行重新建置資料並取得合規來源。
這不是財務、稅務、法律或投資建議。 資料中的稅率、費率、法規門檻雖依 2026 年
（民國 115 年）台灣公開資訊整理，但可能已經過時或有誤。任何實際決策前，
請以主管機關公告為準（財政部、金管會、勞動部、衛福部、中央銀行、全國法規資料庫）。
內容為程式化合成，非真實考題逐字收錄。 題目由模板與參數取樣組合而成，… See the full description on the dataset page: https://huggingface.co/datasets/Simon-Liu/tw-finance-function-call-reasoning.Arabic_Function_Calling
Arabic Function Calling Dataset (50K+ Samples)
مجموعة بيانات استدعاء الدوال العربية
أول وأكبر مجموعة بيانات عربية متخصصة في استدعاء الدوال (Function Calling) تغطي جميع اللهجات العربية الرئيسية والمجالات الحياتية المهمة.
Dataset Description
This is the first comprehensive Arabic function calling dataset designed for training and evaluating LLMs on Arabic tool use capabilities. The dataset covers:
5 Arabic Dialects: MSA (Modern Standard Arabic), Egyptian… See the full description on the dataset page: https://huggingface.co/datasets/Sellopale/Arabic_Function_Calling.hermes-function-calling-v1
Hermes Function-Calling V1
This dataset is the compilation of structured output and function calling data used in the Hermes 2 Pro series of models.
This repository contains a structured output dataset with function-calling conversations, json-mode, agentic json-mode and structured extraction samples, designed to train LLM models in performing function calls and returning structured output based on natural language instructions. The dataset features various conversational scenarios… See the full description on the dataset page: https://huggingface.co/datasets/giovannioliveira/hermes-function-calling-v1.hermes-function-calling-v1
Hermes Function-Calling V1
This dataset is the compilation of structured output and function calling data used in the Hermes 2 Pro series of models.
This repository contains a structured output dataset with function-calling conversations, json-mode, agentic json-mode and structured extraction samples, designed to train LLM models in performing function calls and returning structured output based on natural language instructions. The dataset features various conversational scenarios… See the full description on the dataset page: https://huggingface.co/datasets/sahilstar/hermes-function-calling-v1.