datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.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.xlam-function-calling-60k-hermesfunction-calling-chatml
Dataset Card for "function-calling-chatml"
Converted glaiveai/Glaive-function-calling-v2 to chatml format.
Example entry
[ { "from": "system", "value": "You are a helpful assistant with access to the following functions. Use them if required -{\n \"name\": \"create_contact\",\n \"description\": \"Create a new contact\",\n \"parameters\": {\n \"type\": \"object\",\n \"properties\": {\n \"name\": {\n \"type\": \"string\",\n \"description\": \"The name of the contact\"\n }… See the full description on the dataset page: https://huggingface.co/datasets/Locutusque/function-calling-chatml.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
Salesforce-xlam-function-calling-60kglaive-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.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.Universal-glaive-function-calling-v2
Dataset Card for "Universal-glaive-function-calling-v2"
More Information needed
function-calling-v0.2-with-r1-cotThis dataset is a modified version of Salesforce/xlam-function-calling-60k, incorporating reasoning chains generated by deepseek-ai/DeepSeek-R1-Distill-Llama-8B.
glaive-function-calling-v2-formatted
Dataset Card for "glaive-function-calling-v2-formatted"
More Information needed
hermes-function-calling-thinking-V1function-calling-eval-dataset-v0The hf dataset contains 2 evaluation datasets
single_turn - The converstaion length for this evaluation dataset is 2. It consists of a user ask followed by a function call by assistant.
multi_turn - The conversation length is variable here but contains a combination of user messages, assistant function calls, assistant messages & tool responses.
Information about the columns
tools - List of functions/tools with specs in JSON format. This is the list of functions the model has to choose from… See the full description on the dataset page: https://huggingface.co/datasets/fireworks-ai/function-calling-eval-dataset-v0.pythonic-function-calling
Pythonic Function Calling Dataset
This dataset contains synthetic data used for training Pythonic function calling models Dria-Agent-a-3B and Dria-Agent-a-7B.
Dria is a python framework to generate synthetic data on globally connected edge devices with 50+ models. See the network here
Dataset Summary
The dataset includes various examples of function calling scenarios, ranging from simple to complex multi-turn interactions.
It was generated synthetically using the… See the full description on the dataset page: https://huggingface.co/datasets/driaforall/pythonic-function-calling.Salesforce-xlam-function-calling-60kgemma3-pythonic-function-tool-calling-v1gemma-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.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.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.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.
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.glaive-function-calling-v2-formatted
original dataset: glaiveai/glaive-function-calling-v2
{'system_message': 'You are a helpful assistant with access to the following functions. Use them if required -',
'function_description': '{\n "name": "get_random_quote",\n "description": "Get a random quote",\n "parameters": {}\n}',
'conversations': [{'content': 'Hi, can you help me with something?',
'role': 'user'},
{'content': "Of course! I'm here to assist you. What do you need help with?",
'role': 'assistant'}… See the full description on the dataset page: https://huggingface.co/datasets/heegyu/glaive-function-calling-v2-formatted.glaive-function-calling-v2-sharegpt
Dataset Card for "glaive-function-calling-v2-sharegpt"
This dataset takes the glaive/glaive-function-calling-v2 dataset and formats it with ShareGPT using Lilac
The accompanying notebook can be found here.
The original columns "system" and "chat" still exist on the dataset.
There are 4 types of roles in the ShareGPT format:
system
user
human
function call
The original dataset has a column called 'chat' with the following structure:
USER: Hi, I need help with calculating a tip. My… See the full description on the dataset page: https://huggingface.co/datasets/lilacai/glaive-function-calling-v2-sharegpt.fcd
RFCD: Registry-based Function Calling Dataset
RFCD is a registry-based dataset for evaluating function-calling behavior under realistic scaling conditions. Each instance consists of a user query, a registry of candidate function schemas, and a ground-truth target indicating either the correct function call or abstention. By varying registry size while keeping the task fixed, RFCD isolates the effect of scale on tool selection and argument generation.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/functioncalling/fcd.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.function-calling
function-calling
The purpose of this dataset is to give function calling abilities to your LLM.
Derived from hypervariance/function-calling-sharegpt with a system prompt cleanup and other minor fixes.
Prompt format
With functions
## Configuration
Functions: enabled
## Available Functions
{ ... }
{ ... }
---
You are a helpful assistant.
Without functions
## Configuration
Functions: disabled
---
You are a helpful assistant.
Function… See the full description on the dataset page: https://huggingface.co/datasets/MathAndMagic/function-calling.glaive-function-calling-v2-parsed-with-reasoninghermes-function-calling-v1-allturkish-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.glm52-datagen-r11-100-agentic-function-calling-pivot-v2-traces