fast.ai¶
| Field | Value |
|---|---|
| Description | fast.ai datasets are a curated collection of commonly used machine learning datasets that are: - Pre-hosted (mostly on AWS Open Data) - Standardized in format - Integrated directly into the fastai library - Their goal is to remove the friction of finding, downloading, and preprocessing data so you can focus on modeling. Dataset Include: - image_classification_datasets: CALTECH_101, CIFAR_100, CUB_200_2011, FOOD, MNIST, FLOWERS, PETS, CARS - image_localization_datasets: LSUN_BEDROOMS, BIWI_HEAD_POSE, CAMVID, CAMVID_TINY, PASCAL_2007, PASCAL_2012 - kaggle_competitions_download_dogs_vs_cats: DOGS - main_datasets: ADULT_SAMPLE, BIWI_SAMPLE, CIFAR, COCO_SAMPLE, COCO_TINY, HUMAN_NUMBERS, IMAGENETTE, IMAGENETTE_160, IMAGENETTE_320, IMAGEWANG, IMAGEWANG_160, IMAGEWANG_320, IMAGEWOOF, IMAGEWOOF_160, IMAGEWOOF_320, IMDB, IMDB_SAMPLE, MNIST_SAMPLE, MNIST_TINY, MNIST_VAR_SIZE_TINY, ML_SAMPLE, PLANET_SAMPLE, PLANET_TINY - nlp_datasets: AG_NEWS, AMAZON_REVIEWS, AMAZON_REVIEWS_POLARITY, DBPEDIA, MT_ENG_FRA, SOGOU_NEWS, WIKITEXT, WIKITEXT_TINY, YAHOO_ANSWERS, YELP_REVIEWS, YELP_REVIEWS_POLARITY - pretrained_models: OPENAI_TRANSFORMER, WT103_BWD, WT103_FWD - skin_lesion_datasets: SIIM_SMALL, TCGA_SMALL |
| Folder | /datasets/ai/fast.ai |
| Discipline | AI / Machine Learning |
| DOI | 10.3390/info11020108 |
| Link | Access Data |
| Public | True |
| Publication Date | 2020-02-11 |
| Downloaded | 2026-03-07 |
| Data Type | compressed tar archive (tgz) |
| Dataset Size | 71G (compressed) |
| Number of Files | - caltech_101.tgz: 9248 - cifar100.tgz: 60243 - CUB_200_2011.tgz: 12005 - food-101.tgz: 101121 - mnist_png.tgz: 70023 - oxford-102-flowers.tgz: 8194 - oxford-iiit-pet.tgz: 25869 - stanford-cars.tgz: 16189 - bedroom.tgz: 307494 - biwi_head_pose.tgz: 31455 - camvid.tgz: 1408 - camvid_tiny.tgz: 204 - pascal_2007.tgz: 10398 - pascal_2012.tgz: 25451 - dogscats.tgz: 37541 - adult_sample.tgz: 5 - biwi_sample.tgz: 203 - cifar10.tgz: 60024 - coco_sample.tgz: 21841 - coco_tiny.tgz: 203 - human_numbers.tgz: 3 - imagenette2-160.tgz: 13420 - imagenette2-320.tgz: 13418 - imagenette2.tgz: 13418 - imagewang-160.tgz: 26382 - imagewang-320.tgz: 26382 - imagewang.tgz: 26382 - imagewoof2-160.tgz: 12978 - imagewoof2-320.tgz: 12978 - imagewoof2.tgz: 12978 - imdb_sample.tgz: 2 - imdb.tgz: 100027 - mnist_sample.tgz: 14442 - mnist_tiny.tgz: 1439 - mnist_var_size_tiny.tgz: 1440 - movie_lens_sample.tgz: 2 - planet_sample.tgz: 1003 - planet_tiny.tgz: 203 - ag_news_csv.tgz: 5 - amazon_review_full_csv.tgz: 4 - amazon_review_polarity_csv.tgz: 4 - dbpedia_csv.tgz: 5 - giga-fren.tgz: 3 - sogou_news_csv.tgz: 5 - wikitext-103.tgz: 3 - wikitext-2.tgz: 3 - yahoo_answers_csv.tgz: 5 - yelp_review_full_csv.tgz: 4 - yelp_review_polarity_csv.tgz: 4 - transformer.tgz: 3 - wt103-bwd.tgz: 3 - wt103-fwd.tgz: 3 - siim_small.tgz: 255 - tcga_small.tgz: 120 |
| Usage | $ module avail |
| Usage Policy Link | |
| Usage Policy | |
| Citation | To cite fast.ai datasets, you should cite the original dataset creator (e.g., ImageNet, Oxford-IIIT) and acknowledge the fast.ai/AWS collection. https://docs.fast.ai/data.external.html |
| BibTeX | 📜 View BibTeX citation@article{howard2020fastai, |