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README.md

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-iNatAg is a large-scale dataset derived from the iNaturalist dataset, designed for species classification and crop/weed classification in agricultural and ecological applications. It consists of 2,959 species with a breakdown of 1,986 crop species and 973 weed species.The dataset contains a total of 4,720,903 images, making it one of the largest and most diverse datasets available for plant species identification and classification.
+**iNatAg** is a large-scale dataset derived from the iNaturalist dataset, designed for species classification and crop/weed classification in agricultural and ecological applications. It consists of 2,959 species with a breakdown of 1,986 crop species and 973 weed species.The dataset contains a total of 4,720,903 images, making it one of the largest and most diverse datasets available for plant species identification and classification.
 
-iNatAg is also released as part of the [AgML](https://github.com/Project-AgML/AgML) dataset collection, with support for filtering by species, genus, or family and direct data loading through a streamlined API. The associated paper can be found at https://www.arxiv.org/abs/2503.20068.
+We also developed a subset of the iNatAg dataset for smaller-scale applications, which we call [iNatAg-mini](https://huggingface.co/datasets/Project-AgML/iNatAg-mini). It contains 560,844 images, created by sampling up to 200 images per species from the full iNatAg dataset. These datasets can then be used in standard agricultural machine learning workflows, enabling the development of extensive applications using this data.
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+iNatAg and iNatAg-mini are also released as part of the [AgML](https://github.com/Project-AgML/AgML) dataset collection, with support for filtering by species, genus, or family and direct data loading through a streamlined API. The associated paper can be found at https://www.arxiv.org/abs/2503.20068.
 ## Installation
 
 To install the latest release of AgML, run the following command: