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.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, and… See the full description on the dataset page: https://huggingface.co/datasets/lockon/xlam-function-calling-60k.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… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/xlam-function-calling-60k.xlam-function-calling-60kglaive-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.
Nemotron-RL-Agentic-Function-Calling-Pivot-v1
Dataset Description:
This is a RL dataset for general function-calling by utilizing existing expert tool-use trajectories. We pose each assistant step of the trajectory as a separate behavior cloning problem where the policy model is incentivized to match the tool call choices of the expert model.
This dataset is released as part of NVIDIA NeMo Gym, a framework for building reinforcement learning environments to train large language models. NeMo Gym contains a growing collection… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-RL-Agentic-Function-Calling-Pivot-v1.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.xlam-function-calling-60k-shareGPTShareGPT converted version of 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.glm-5.3-flash-function-calling
GLM-5.3-Flash Function Calling (synthetic)
A synthetic function-calling dataset generated with zai-org/GLM-5.3-Flash via Hugging Face Inference Providers.
513 examples in 8 domains: weather, calendar, finance, travel, e-commerce, devops, smart home, communication.
Categories: single-turn tool calls, parallel/multiple calls in one turn, multi-turn trajectories with tool results, and no-tool-needed turns.
Format: OpenAI-style — each row has tools (JSON-schema function… See the full description on the dataset page: https://huggingface.co/datasets/Rallex3/glm-5.3-flash-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/interstellarninja/hermes-function-calling-v1.Function_Calling_Unfilteredagentmujo-function-calling
agentmujo-function-calling (v0.1.0 — 1252 uzorka)
Ručno dizajniran kanonski skup za function calling na bosanskom jeziku
(ijekavica), dio AgentMujo Training Frameworka
(configs/tools.yaml je Single Source of Truth za alate).
Verzija: 0.1.0 · Uzoraka: 1252 (split 983/128/141) · Jezik: bs-ijekavica
Format: JSONL; svaki red: id, version, language, task, difficulty, enable_thinking, messages[] (user/assistant/tool + tool_calls[]), metadata{}
(schema: schemas/dataset.schema.json u… See the full description on the dataset page: https://huggingface.co/datasets/shaban2024/agentmujo-function-calling.function_callingnarrative-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.llama-2-oai-function-callingmulti-hop-qa-function-calling-format-V1.0This dataset is converted from khaimaitien/qa-expert-multi-hop-qa-V1.0 to OpenAI function calling format.
Each data point is a list of messages with role=user, assistant or function:
message that role=user, content is the question
message that role=assistant, content is not None, function_call is None: --> assistant responds with text only
message that role=assistant and function_call is not None --> assistant asks to execute a function call
function_call is of the form: {"name": "retrieve"… See the full description on the dataset page: https://huggingface.co/datasets/khaimaitien/multi-hop-qa-function-calling-format-V1.0.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.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
🛑 Most Function-Calling Failures Are Not Schema Failures. They Are State Failures.
The model believes the world is still valid — when reality has already changed.
エージェントの事故は「ツールの失敗」ではなく「古い状態を信じたまま正常終了する」ことで起きます。本データセットは多輪ツール呼び出し・エラー復帰・検証ステップを日本語で学習させます。
Japanese Function Calling Dataset — Official Open‑Source Evaluation Package (50 Rows Subset) by springofwindslabs
Full production volumes (1,000-row standard and 2,300+ row non-overlapping extended lots), commercial licensing… See the full description on the dataset page: https://huggingface.co/datasets/springofwindslabs/function-calling-ja-trial.function-calling-en-trial
🛑 Most Function-Calling Failures Are Not Schema Failures. They Are State Failures.
The model believes the world is still valid — when reality has already changed.
It calls the right tool with stale beliefs, gets "success", and moves on. That is how agents silently corrupt production state.
This dataset trains argument-level correctness under changing state: multi-turn tool use, error recovery, and explicit verification steps — not just happy-path calls.
Function Calling Dataset… See the full description on the dataset page: https://huggingface.co/datasets/springofwindslabs/function-calling-en-trial.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.glaive-function-calling-v2-llama-factory-convertThis is a converted dataset for https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2 that allows sft in https://github.com/hiyouga/LLaMA-Factory for function calling fine tuning.
You need to add the following to the datasets.json file, and changed the file_name to your local path.
"glaive-function-calling-v2": {
"file_name": "./glaive-function-calling-v2/simple-function-calling-v2_converted.json",
"columns": {
"prompt": "instruction",
"query": "input"… See the full description on the dataset page: https://huggingface.co/datasets/Yhyu13/glaive-function-calling-v2-llama-factory-convert.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.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.function-calling-pt-pt
function-calling-pt-pt
English function-calling conversations translated into European Portuguese (pt-PT). Only the natural-language turns are translated. Tool definitions, calls and tool results stay in English, exactly as in the source, so a model learns to take a request in Portuguese and call an English API with the right arguments.
Source
License
Conversations
Kept after checks
xlam
cc-by-4.0
59,221
100%
hermes
apache-2.0
1,091
99%
toolace
apache-2.0
10,553… See the full description on the dataset page: https://huggingface.co/datasets/jgalego/function-calling-pt-pt.small_function_callingVietnamese-Salesforce-xlam-function-calling-60k-gg-translatedglm-5.3-flash-function-calling
GLM-5.3-Flash Function Calling (multi-turn agentic, Coding/DevOps)
Synthetic multi-turn agentic function-calling conversations generated with
zai-org/GLM-5.3-Flash via HF Inference Providers.
Format: OpenAI chat messages with a tools array of JSON-schema function definitions.
Assistant turns carry tool_calls; tool outputs are model-simulated (role: "tool").
Domains: {"containers": 75, "lint_build": 49, "git": 74, "deploy": 70, "shell": 69, "code_review": 71, "ci": 35… See the full description on the dataset page: https://huggingface.co/datasets/closestfriend/glm-5.3-flash-function-calling.