datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
new-york-smells
New York Smells: A Large Multimodal Dataset for Olfaction
While olfaction is central to how animals perceive the world, this rich chemical
sensory modality remains largely inaccessible to machines. One key bottleneck is the
lack of diverse, multimodal olfactory data collected in natural settings. We present
New York Smells, a large-scale dataset of paired image and olfactory signals
captured in-the-wild. Our dataset contains 7,000 smell-image pairs from 3,500 distinct
objects… See the full description on the dataset page: https://huggingface.co/datasets/cvlab/new-york-smells.plant-disease-trainSmellNet
SmellNet
SmellNet is a comparatively large dataset for sensor-based machine olfaction: real-world smell measurements collected from a compact array of low-cost metal-oxide (MOX) gas sensors.
The dataset supports:
single-substance recognition from multichannel sensor time series
mixture distribution prediction from odor mixtures
cross-modal learning with paired GC-MS-derived chemistry priors
research on temporal modeling for smell sensing
The accompanying paper introduces… See the full description on the dataset page: https://huggingface.co/datasets/DeweiFeng/SmellNet.ML-Python-Code-SmellsSmellBench
SmellBench: Towards Fine-Grained Evaluation of Code Agents on Refactoring Tasks
Dataset Summary
SmellBench is a benchmark designed to evaluate whether code agents can detect and refactor bad code (code smells). Each instance represents a validated code smell injection case constructed from real-world open-source repositories, enabling fine-grained assessment of code agents' refactoring capabilities.
Supported Tasks
Code Refactoring: Given code with… See the full description on the dataset page: https://huggingface.co/datasets/critical88/SmellBench.SmellNet
SmellNet
SmellNet is a comparatively large dataset for sensor-based machine olfaction: real-world smell measurements collected from a compact array of low-cost metal-oxide (MOX) gas sensors.
The dataset supports:
single-substance recognition from multichannel sensor time series
mixture distribution prediction from odor mixtures
cross-modal learning with paired GC-MS-derived chemistry priors
research on temporal modeling for smell sensing
The accompanying paper introduces… See the full description on the dataset page: https://huggingface.co/datasets/Hobin0329/SmellNet.malerecognitionflower_smellshuberman_lab_Dr._Noam_Sobel_How_Smells_Influence_Our_Hormones_Health__Behaviorhuberman_lab_How_Smell_Taste__Pheromone-Like_Chemicals_Control_YouSmellLearningcodes-for-test-smellscode_smellSmellDBhl_contract_smellsautol_contract_smellsitems_prompt_fulldescriptive_contract_smellsdescriptive_textual_contract_smellscode-smell-datasetitems_prompt_litehuberman_lab_Dr__Noam_Sobel_How_Smells_Influence_Our_Hormones_Health__Behaviorts-detect-test-smell-gemini-explainedtest-smells-with-source-code