datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
iNaturalist2021
iNaturalist 2021
This dataset is collected from https://github.com/visipedia/inat_comp/tree/master/2021
i1-inaturalist-tfrecordi1: A Simple and Fully Open Recipe for Strong Text-to-Image Models
Boya Zeng, Tianze Luo, Shu Pu, Jucheng Shen, Taiming Lu, Gabriel Sarch, Zhuang Liu
Princeton University
[arXiv][code][model][project page]
Overview
To prepare the dataset for training, we store the image-caption pairs as TFRecords.
This HuggingFace dataset contains the TFRecords corresponding to the inaturalist dataset at 256×256 resolution.
It also serves as an example of what a dataset processed using… See the full description on the dataset page: https://huggingface.co/datasets/zlab-princeton/i1-inaturalist-tfrecord.inaturalist-s3-massiveSnapshot of the iNaturalist dataset from 2026-03-27.
NOTE This dataset only contains images with license CC0 or CC-BY.
The CSV files were retrieved using
aws s3 --no-sign-request --region eu-central-1 cp s3://inaturalist-open-data/photos.csv.gz photos.csv.gz
aws s3 --no-sign-request --region eu-central-1 cp s3://inaturalist-open-data/taxa.csv.gz taxa.csv.gz
aws s3 --no-sign-request --region eu-central-1 cp s3://inaturalist-open-data/observations.csv.gz observations.csv.gz
then this dataset… See the full description on the dataset page: https://huggingface.co/datasets/philipp-zettl/inaturalist-s3-massive.inaturalist-enriched
Enriched iNaturalist dataset from 2026-03-27.
This dataset is based on philipp-zettl/inaturalist-s3-massive.
The data was enriched using the ./enrich.py script inside the repository.
It contains the following features
photo_id: The original ID of the photo inside the inaturalist dataset
observation_uuid: The observation's UUID
image: The actual image content
taxon_id: The ID of the taxonomy
species_name: The name of the species inside the image
taxonomic_rank: The type of taxonomic rank… See the full description on the dataset page: https://huggingface.co/datasets/philipp-zettl/inaturalist-enriched.wds_inaturalistinaturalist
Dataset Description
The iNaturalist dataset is a large-scale species classification dataset for fine-grained recognition. This split is derived from the OpenOOD benchmark OOD evaluation splits.
Homepage: https://github.com/visipedia/inat_comp
OpenOOD Benchmark: https://github.com/Jingkang50/OpenOOD/
Citation
@inproceedings{vanhorn2018inaturalist,
title={The iNaturalist species classification and detection dataset},
author={Van Horn, Grant and others}… See the full description on the dataset page: https://huggingface.co/datasets/torch-uncertainty/inaturalist.iNaturalist-2017inaturalist-bbsinaturalistinaturalist_1kinaturalist
Dataset Card for inaturalist
This dataset is comprised of 9549 observations that were posted on the iNaturalist app. iNaturalist is a website and app that 'aims to provide a crowd sourced identification system' for plants, insects, and animals.
Dataset Details
For each of the 9549 observations included in this dataset, there is information about the quality ('quality_grade') of the observation and associated photo(s),
a species name ('species_guess') along with a… See the full description on the dataset page: https://huggingface.co/datasets/ba188/inaturalist.iNaturalist_v2
Dataset Card for Dataset Name
This dataset is comprised of 1,079 observations that were posted on the iNaturalist app. iNaturalist is a website and mobile app that 'aims to
provide a crowd-sourced identification system' for plants, insects, and animals.
Dataset Details
Dataset Description
For each of the 1,079 observations included in this dataset, there is information about the quality of the associated image (quality_grade), a species label… See the full description on the dataset page: https://huggingface.co/datasets/ba188/iNaturalist_v2.inaturalist2018inaturalist-2024-2.8k-claude-opus-5-recaptioned
iNaturalist 2024 2.8K — Claude Opus 5 Recaptioned
This is a 2,824-image derivative subset of iNaturalist 2024 (iNat24), distributed through the INQUIRE project, selected through the inaturalist portion of zlab-princeton/i1-captions. It is not the complete 4.8-million-image iNat24 training set.
Every image has one newly generated, detailed English caption. The recaptioning was performed with Claude Opus 5 via Claude Code on August 2, 2026. The image was the primary evidence; the… See the full description on the dataset page: https://huggingface.co/datasets/sirus/inaturalist-2024-2.8k-claude-opus-5-recaptioned.inaturalistiNaturalist_mortality_records_12Apr2025inaturalist-12kinaturalist-taxonomy-multimodalinaturalist_valinaturalist_sorted_with_labeliNaturalist-CoDA-Subsetinaturalist
iNaturalist QA Dataset
This repository contains the complete iNaturalist dataset prepared for a question-answering / classification task. It includes every example from the original splits where:
The taxon column was not null.
The image at the provided url was reachable and successfully downloaded.
All images are stored locally, so you can train and evaluate without relying on external URLs.
🔗 Original Dataset Source
The original dataset can be found at:… See the full description on the dataset page: https://huggingface.co/datasets/Mhmd08/inaturalist.iNaturalist-CoDA-Subsetinaturalist-open-dataset-5mapiarist-inaturalist-bees
Apiarist iNaturalist bee photos
Honey-bee (Apis mellifera) photos scraped from the iNaturalist API as
training context for Apiarist — a fully-offline AI hive frame
inspector built for the Build Small Hackathon.
Composition
584 photos of Apis mellifera observations
Filtered to permissively-licensed images (CC0, CC-BY, CC-BY-SA, CC-BY-NC, etc.)
Most are forager bees on flowers; useful as bee context for VLM prompting
Files
images/ — JPEG photos… See the full description on the dataset page: https://huggingface.co/datasets/maryammeda/apiarist-inaturalist-bees.inaturalist_scoreinaturalist_sortedinaturalist-taxonomy-multimodal-sampleinaturalist_annotationsinaturalist
Dataset Description
The iNaturalist dataset is a large-scale species classification dataset for fine-grained recognition. This split is derived from the OpenOOD benchmark OOD evaluation splits.
Homepage: https://github.com/visipedia/inat_comp
OpenOOD Benchmark: https://github.com/Jingkang50/OpenOOD/
Citation
@inproceedings{vanhorn2018inaturalist,
title={The iNaturalist species classification and detection dataset},
author={Van Horn, Grant and others}… See the full description on the dataset page: https://huggingface.co/datasets/XuZhan1/inaturalist.