datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/google/mobile-actions.mobile-actions-ita
Dataset Card: Mobile Actions (Italian Adaptation for Function Calling)
Overview
This dataset is an Italian adaptation of the original Google Mobile Actions dataset, designed to train lightweight models for on-device function calling. It preserves the original tool-calling schema in English while translating user interactions and contextual instructions into Italian.
The goal is to enable models to map natural language instructions in Italian to structured function calls… See the full description on the dataset page: https://huggingface.co/datasets/Mattimax/mobile-actions-ita.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/0xmoose0xmoose0xmoose/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/burancel/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/jeffbrian/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/lanneret/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/muralcode/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/HexQuant/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/Macarao26722/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/amine-khelif/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/mindchain/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/tatan2/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/JesseJelinek/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/deougege/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/Rendy45/mobile-actions.liquidchat-mobile-actions-2026-02-24
liquidchat-mobile-actions-2026-02-24
Chat history dataset exported from LiquidChat mobile app.
Dataset Description
This dataset contains conversations with a mobile-actions fine-tuned LLM, including tool calls (flashlight, calendar, email, maps, contacts, wifi) and their results.
Usage
from datasets import load_dataset
dataset = load_dataset("kshitijthakkar/liquidchat-mobile-actions-2026-02-24")
Created by: kshitijthakkar
Exported from: LiquidChat
License:… See the full description on the dataset page: https://huggingface.co/datasets/kshitijthakkar/liquidchat-mobile-actions-2026-02-24.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/ettilapse/mobile-actions.mobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/Rendra86318/mobile-actions.liquidchat-mobile-actions-2026-02-23
liquidchat-mobile-actions-2026-02-23
Chat history dataset exported from LiquidChat mobile app.
Dataset Description
This dataset contains conversations with a mobile-actions fine-tuned LLM, including tool calls (flashlight, calendar, email, maps, contacts, wifi) and their results.
Usage
from datasets import load_dataset
dataset = load_dataset("kshitijthakkar/liquidchat-mobile-actions-2026-02-23")
Created by: kshitijthakkar
Exported from: LiquidChat
License:… See the full description on the dataset page: https://huggingface.co/datasets/kshitijthakkar/liquidchat-mobile-actions-2026-02-23.mobile-actions2
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/0xmoose0xmoose0xmoose/mobile-actions2.mobile-actionssmarthome-mobile-actionsmobile-actions
Mobile Actions: A Dataset for On-Device Function Calling
The dataset contains conversational traces designed to train lightweight models (such as FunctionGemma 270M) to translate natural language instructions into executable function calls for Android OS system tools.
Dataset Format
The dataset is provided in JSONL format. Each line represents a data sample. The
dataset is pre-split into training and evaluation sets. This distinction is
denoted by the metadata field… See the full description on the dataset page: https://huggingface.co/datasets/R1Sh111/mobile-actions.
