datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
code-tool-calling-functiongemma
Code Tool Calling Dataset (FunctionGemma Format)
A curated dataset of coding-focused tool-calling examples formatted for FunctionGemma-style training as demonstrated in google/mobile-actions.
Dataset Overview
Total: 82,406 examples (85% train / 15% validation split per subset)
Subsets
Config Name
Original Dataset
Original Subset
Train
Validation
Total
ToolRM
ibm-research/ToolRM-train-data
train
44,293
7,823
52,116
Toucan-1.5M-SFT… See the full description on the dataset page: https://huggingface.co/datasets/eacortes/code-tool-calling-functiongemma.functiongemma-prepaid-cards-tool-calling
FunctionGemma Prepaid-Cards Tool-Calling Dataset
Synthetic training data for fine-tuning google/functiongemma-270m-it so it can
recognize chat intents for buying prepaid cards, checking balances, and viewing
transaction history, and emit the correct tool call.
Tools
Tool
Purpose
purchase_card(amount, card_type, email?, currency?)
Buy a Digital Prepaid Visa or Virtual Prepaid Mastercard
get_card_balance(card_number)
Check the balance of a card… See the full description on the dataset page: https://huggingface.co/datasets/Qrzysztof/functiongemma-prepaid-cards-tool-calling.arabic-tooluse-functiongemma-v1
Arabic Tool Use — FunctionGemma Format (v1)
This dataset is a processed Arabic tool-use / function-calling dataset from this dataset: HeshamHaroon/Arabic_Function_Calling converted into a FunctionGemma-friendly format for supervised finetuning.
The main goal is to train a model that, given a user request in Arabic (multiple dialects), predicts a single tool call with JSON arguments following the provided tool schema.
What’s inside
Splits
train
test… See the full description on the dataset page: https://huggingface.co/datasets/metga97/arabic-tooluse-functiongemma-v1.functiongemma-prepaid-cards-tool-calling-v2
FunctionGemma Prepaid-Cards Tool-Calling Dataset
Synthetic training data for fine-tuning google/functiongemma-270m-it so it can
recognize chat intents for buying prepaid cards, checking balances, and viewing
transaction history, and emit the correct tool call.
Tools
Tool
Purpose
purchase_card(amount, card_type, email?, currency?)
Buy a Digital Prepaid Visa or Virtual Prepaid Mastercard
get_card_balance(card_number)
Check the balance of a card… See the full description on the dataset page: https://huggingface.co/datasets/Qrzysztof/functiongemma-prepaid-cards-tool-calling-v2.functiongemma-agent-sft
FunctionGemma Agent SFT Dataset
Training data for fine-tuning FunctionGemma models on agentic tool-calling tasks, designed for use with llama-agent.
Format
Uses FunctionGemma's native format with <escape> delimiters (not JSON):
<start_of_turn>developer
You are a model that can do function calling with the following functions
<start_function_declaration>declaration:read_file{...}<end_function_declaration>
...
<end_of_turn>
<start_of_turn>user
Fix the typo in config.json… See the full description on the dataset page: https://huggingface.co/datasets/victor/functiongemma-agent-sft.network-agent-functiongemma-en-es
Network Agent (FunctionGemma) EN/ES Tool-Calling Dataset
Synthetic two-turn tool-calling dataset for a small on-device network assistant, exported in the
functiongemma_tool_calling format and compatible with the Google/Hugging Face FunctionGemma flow
(apply_chat_template(messages, tools=tools)).
The agent answers user questions about the home network by calling one of three tools on the first
turn and then producing a short natural-language answer on the second turn, using the… See the full description on the dataset page: https://huggingface.co/datasets/lucasllfsQ/network-agent-functiongemma-en-es.functiongemma-python-functions
FunctionGemma Python Function Calling Dataset
This dataset contains training examples for fine-tuning FunctionGemma 270M to perform Python function calling tasks.
Dataset Details
Dataset Description
This dataset is designed for training FunctionGemma models to translate natural language queries into structured function calls. Each example contains:
Developer message: System prompt describing available functions
User message: Natural language query
Assistant… See the full description on the dataset page: https://huggingface.co/datasets/sandeeppanem/functiongemma-python-functions.