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.

FiftyOne QA 14k Dataset

  Overview

This dataset is derived from the FiftyOne Function Calling 14k dataset and is designed to train AI assistants to understand and answer questions about FiftyOne's functionality.

  Purpose

Train AI models to understand FiftyOne-related queries Provide examples of FiftyOne syntax Map natural language questions to appropriate FiftyOne code snippets Demonstrate correct usage for FiftyOne functions and method calls

This dataset was… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/fiftyone-qa-pairs-14k.

Dataset Card for quickstart

This is a FiftyOne dataset with 200 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo from fiftyone.utils.huggingface import load_from_hub

Load the dataset

Note: other available arguments include 'max_samples', etc

dataset = load_from_hub("manushreeg/my-quickstart-dataset")

Launch the App

session = fo.launch_app(dataset)

  Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/manushreeg/my-quickstart-dataset.

Dataset Card for new_test_dataset5

This is a FiftyOne dataset with 1 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo from fiftyone.utils.huggingface import load_from_hub

Load the dataset

Note: other available arguments include 'max_samples', etc

dataset = load_from_hub("Abeyankar/class_mapping_source_test_dataset")

Launch the App

session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/Abeyankar/class_mapping_source_test_dataset.

Dataset Card for Data-Centric-Visual-AI-Train-Set

This is a FiftyOne dataset with 30,000 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo import fiftyone.utils.huggingface as fouh

Load the dataset

Note: other available arguments include 'max_samples', etc

dataset = fouh.load_from_hub("Voxel51/Data-Centric-Visual-AI-Challenge-Train-Set")

Launch the App

session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Data-Centric-Visual-AI-Challenge-Train-Set.

FiftyOne Embeddings Dataset

This dataset combines the FiftyOne Q&A and function calling datasets with pre-computed embeddings for fast similarity search.

  Dataset Information

Total samples: 28,118 Q&A samples: 14,069 Function samples: 14,049 Embedding model: text-embedding-3-large Embedding dimension: 3072

  Schema

query: The original question/query text response: The unified response content (either answer text for Q&A or function call text for function… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/fiftyone-embeddings-combined.

Dataset Card for cvpr2024_papers

This is a FiftyOne dataset with 2379 samples. The dataset consists of images of the first page for accepted papers to CVPR 2024, plus their abstract and other metadata.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo import fiftyone.utils.huggingface as fouh

Load the dataset

Note: other available arguments include 'split', 'max_samples', etc

dataset =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/CVPR_2024_Papers.

Dataset Card for Food Waste Dataset

This is a FiftyOne dataset with 375 samples focused on food waste analysis and nutritional content detection.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo from fiftyone.utils.huggingface import load_from_hub

Load the dataset

Note: other available arguments include 'max_samples', etc

dataset = load_from_hub("andandandand/food-waste-dataset")

Launch the App… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/food-waste-dataset.

Dataset Card for Lecture Test Set for Coursera MOOC - Hands Data Centric Visual AI

This dataset is the test dataset for the in-class lectures of the Hands-on Data Centric Visual AI Coursera course. This is a FiftyOne dataset with 4159 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo import fiftyone.utils.huggingface as fouh

Load the dataset

Note: other available arguments include… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Coursera_lecture_dataset_test.

📦 FiftyOne-Compatible Multiview Person ReID with Visual Attributes

A curated, attribute-rich person re-identification dataset based on Market-1501, enhanced with:

✅ Multi-view images per person ✅ Detailed physical and clothing attributes ✅ Natural language descriptions ✅ Global attribute consolidation

  📊 Dataset Statistics

Subset Samples

Train 3,181

Query 1,726

Gallery 1,548

Total 6,455

  📥 Installation

Install the required… See the full description on the dataset page: https://huggingface.co/datasets/adonaivera/fiftyone-multiview-reid-attributes.

FiftyOne Embeddings Dataset

This dataset combines the FiftyOne Q&A and function calling datasets with pre-computed embeddings for fast similarity search.

  Dataset Information

Total samples: 28,118 Q&A samples: 14,069 Function samples: 14,049 Embedding model: Qwen/Qwen3-Embedding-0.6B Embedding dimension: 1024

  Schema

query: The original question/query text response: The unified response content (either answer text for Q&A or function call text for function… See the full description on the dataset page: https://huggingface.co/datasets/harpreetsahota/fiftyone-qa-with-qwen-embeddings.

Charitarth/dac-sdc-2024-coco-fiftyone dataset hosted on Hugging Face and contributed by the HF Datasets community

Dataset Card for LVIS-35k

This is a FiftyOne dataset with 35000 samples. NOTE: This is only a 35k sample subset of the full dataset. The notebook recipe for creating this, and the full, dataset can be found here

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo import fiftyone.utils.huggingface as fouh

Load the dataset

Note: other available arguments include 'max_samples', etc

dataset =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/LVIS.

Dataset Card for FishEye8K: A Benchmark and Dataset for Fisheye Camera Object Detection

This is a FiftyOne dataset with 8000 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo from fiftyone.utils.huggingface import load_from_hub

Load the dataset

Note: other available arguments include 'max_samples', etc

dataset = load_from_hub("Voxel51/fisheye8k")

Launch the App

session =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/fisheye8k.

Dataset Card for Multimodal Mind2Web "Cross-Task" Test Split

Note: This dataset is the test split of the Cross-Task dataset introduced in the paper.

This is a FiftyOne dataset with 1338 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo from fiftyone.utils.huggingface import load_from_hub

Load the dataset

Note: other available arguments include 'max_samples', etc

dataset =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/mind2web_multimodal_test_task.

Dataset Card for UnCommon Objects in 3D

This is a FiftyOne dataset with 52 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo from fiftyone.utils.huggingface import load_from_hub

Load the dataset

Note: other available arguments include 'max_samples', etc

dataset = load_from_hub("Voxel51/uco3d")

Launch the App

session = fo.launch_app(dataset)

  Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/uco3d.

Dataset Card for Homework Training Set for Coursera MOOC - Hands Data Centric Visual AI

This dataset is the training dataset for the homework assignments of the Hands-on Data Centric AI Coursera course. This is a FiftyOne dataset with 18287 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo import fiftyone.utils.huggingface as fouh

Load the dataset

Note: other available arguments include… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Coursera_homework_dataset_train.

Dataset Card for ScreenSpot-Pro

This is a FiftyOne dataset with 1581 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo from fiftyone.utils.huggingface import load_from_hub

Load the dataset

Note: other available arguments include 'max_samples', etc

dataset = load_from_hub("Voxel51/ScreenSpot-Pro")

Launch the App

session = fo.launch_app(dataset)

  Dataset Details… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/ScreenSpot-Pro.

Dataset Card for GUIAct Web-Single Dataset - Test Set

This is a FiftyOne dataset with 1410 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo from fiftyone.utils.huggingface import load_from_hub

Load the dataset

Note: other available arguments include 'max_samples', etc

dataset = load_from_hub("Voxel51/guiact_websingle_test")

Launch the App

session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/guiact_websingle_test.

Dataset Card for arcade_combined_export

This is a FiftyOne dataset with 3000 samples.

  Installation

If you haven't already, install FiftyOne: pip install -U fiftyone

  Usage

import fiftyone as fo from fiftyone.utils.huggingface import load_from_hub

Load the dataset

Note: other available arguments include 'max_samples', etc

dataset = load_from_hub("pjramg/arcade_fiftyone")

Launch the App

session = fo.launch_app(dataset)

  ARCADE Combined… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/ARCADE_FO.