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.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.xlam-function-calling-60k-raw
XLAM Function Calling 60k Raw Dataset
This dataset includes train and test splits derived from Salesforce/xlam-function-calling-60k.
Train split size: 95% of the original dataset
Test split size: 5% of the original dataset
function_calling_extended
Trelis Function Calling Dataset
UPDATE: As of Dec 5th 2023, there is a v3 of this dataset now available from here.
Allows models to be fine-tuned for function-calling.
The dataset is human generated and does not make use of Llama 2 or OpenAI!
Contains 59 training and 17 test rows
Based on eight functions: search_bing, search_arxiv, save_chat, read_json_file, list_files, get_current_weather, delete_file, clear_chat
Access this dataset by purchasing a license HERE.
Alternatively… See the full description on the dataset page: https://huggingface.co/datasets/Trelis/function_calling_extended.function_calling_v3
Trelis Function Calling Dataset - VERSION 3
Access this dataset by purchasing a license HERE.
Allows models to be fine-tuned for function-calling.
The dataset is human generated and does not make use of Llama 2 or OpenAI!
The dataset includes 66 training rows, 19 validation rows and 5 test rows (for manual evaluation).
Based on eight functions: search_bing, search_arxiv, save_chat, read_json_file, list_files, get_current_weather, delete_file, clear_chat
Alternatively, you can find… See the full description on the dataset page: https://huggingface.co/datasets/Trelis/function_calling_v3.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.chatml-function-calling-v2
Dataset Conversion
This dataset is a converted version of the Glaive Function Calling v2 dataset, originally hosted on Hugging Face.
Chat Template for Dataset
Description
This chat template is designed to work with this dataset.
Template
chat_template = """{%- set tools = tools if tools is defined else None -%}
{%- set date_string = date_string if date_string is defined else "1 Sep 2024" -%}
{%- set system_message = messages[0].content if… See the full description on the dataset page: https://huggingface.co/datasets/ankush13r/chatml-function-calling-v2.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.python-audio-copilot-training-using-function-knowledge-graphs
Python Copilot Audio Training using Global Functions with Knowledge Graphs
This dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.
Details
Each global function has a question and answer mp3 where one voice reads the question and another voice reads the answer. Both mp3s are stored in the parquet dbytes column and the associated source code file_path… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-audio-copilot-training-using-function-knowledge-graphs.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.xlam-function-calling-60k-raw-augmented
XLAM Function Calling 60k Raw Augmented Dataset
This dataset includes augmented train and test splits derived from product-science/xlam-function-calling-60k-raw.
Train split size: Original size plus augmented data
Test split size: Original size plus augmented data
Augmentation Details
This dataset has been augmented by modifying function names in the original data. Randomly selected function names have underscores replaced with periods at random positions… See the full description on the dataset page: https://huggingface.co/datasets/product-science/xlam-function-calling-60k-raw-augmented.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.
agentmujo-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.python-image-copilot-training-using-function-knowledge-graphs
Python Copilot Image Training using Function Knowledge Graphs
This dataset is a subset of the matlok python copilot datasets. Please refer to the Multimodal Python Copilot Training Overview for more details on how to use this dataset.
Details
Each row contains a png file in the dbytes column.
Rows: 134357
Size: 130.5 GB
Data type: png
Format: Knowledge graph using NetworkX with alpaca text box
Schema
The png is in the dbytes column:
{
"dbytes": "binary"… See the full description on the dataset page: https://huggingface.co/datasets/matlok/python-image-copilot-training-using-function-knowledge-graphs.function_calling_v3_SAMPLE
Trelis Function Calling Dataset - VERSION 3 - SAMPLE
This is a SAMPLE of the v3 dataset available for purchase here.
Features:
Allows models to be fine-tuned for function-calling.
The dataset is human generated and does not make use of Llama 2 or OpenAI!
The dataset includes 66 training rows, 19 validation rows and 5 test rows (for manual evaluation).
Based on eight functions: search_bing, search_arxiv, save_chat, read_json_file, list_files, get_current_weather, delete_file… See the full description on the dataset page: https://huggingface.co/datasets/Trelis/function_calling_v3_SAMPLE.Vietnamese-Locutusque-function-calling-chatml-gg-translatedArabic_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.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.Vietnamese-Salesforce-xlam-function-calling-60k-gg-translatedHome-Assistant-requests-for-intent-detection-and-function-recognition
Home Assistant Requests V2 Dataset
This dataset contains a list of requests and responses for a user interacting with a personal assistant that controls an instance of Home Assistant.
The updated V2 of the dataset is now multilingual, containing data in English, German, French, Spanish, and Polish. The dataset also contains multiple "personalities" for the assistant to respond in, such as a formal assistant, a sarcastic assistant, and a friendly assistant. Lastly, the dataset has… See the full description on the dataset page: https://huggingface.co/datasets/DaftP/Home-Assistant-requests-for-intent-detection-and-function-recognition.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… See the full description on the dataset page: https://huggingface.co/datasets/Cevan340/hermes-function-calling-v1.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.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.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.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.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.
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.