--- dataset_info: features: - name: image dtype: image - name: caption sequence: string - name: sentids sequence: string - name: img_id dtype: string - name: filename dtype: string splits: - name: test num_bytes: 4190829605.876 num_examples: 31783 download_size: 4409506758 dataset_size: 4190829605.876 configs: - config_name: default data_files: - split: test path: data/test-* ---

# Large-scale Multi-modality Models Evaluation Suite > Accelerating the development of large-scale multi-modality models (LMMs) with `lmms-eval` 🏠 [Homepage](https://lmms-lab.github.io/) | 📚 [Documentation](docs/README.md) | 🤗 [Huggingface Datasets](https://huggingface.co/lmms-lab) # This Dataset This is a formatted version of [flickr30k](https://shannon.cs.illinois.edu/DenotationGraph/). It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models. ``` @article{young-etal-2014-image, title = "From image descriptions to visual denotations: New similarity metrics for semantic inference over event descriptions", author = "Young, Peter and Lai, Alice and Hodosh, Micah and Hockenmaier, Julia", editor = "Lin, Dekang and Collins, Michael and Lee, Lillian", journal = "Transactions of the Association for Computational Linguistics", volume = "2", year = "2014", address = "Cambridge, MA", publisher = "MIT Press", url = "https://aclanthology.org/Q14-1006", doi = "10.1162/tacl_a_00166", pages = "67--78", abstract = "We propose to use the visual denotations of linguistic expressions (i.e. the set of images they describe) to define novel denotational similarity metrics, which we show to be at least as beneficial as distributional similarities for two tasks that require semantic inference. To compute these denotational similarities, we construct a denotation graph, i.e. a subsumption hierarchy over constituents and their denotations, based on a large corpus of 30K images and 150K descriptive captions.", } ```