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.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.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.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-sharegptThe glaive-function-calling-v2 dataset in sharegpt format.
You can use it in LLaMA Factory by specifying --dataset glaive_toolcall_100k.
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.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.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.synthetic-pii-function-calling
Dataset Summary
A function calling dataset created by filtering the urchade/synthetic-pii-ner-mistral-v1 dataset.
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-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.text_message_function_calling_open_chatThis is a small synthetic dataset to model a function call for text messaging someone from a cell phone. This has been tested with and used to finetune a set of smaller models and deployed directly on the pixel 8 pro and Fold 4 phones.
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.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.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.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.