# FLAVA

## Overview The FLAVA model was proposed in [FLAVA: A Foundational Language And Vision Alignment Model](https://huggingface.co/papers/2112.04482) by Amanpreet Singh, Ronghang Hu, Vedanuj Goswami, Guillaume Couairon, Wojciech Galuba, Marcus Rohrbach, and Douwe Kiela and is accepted at CVPR 2022. The paper aims at creating a single unified foundation model which can work across vision, language as well as vision-and-language multimodal tasks. The abstract from the paper is the following: *State-of-the-art vision and vision-and-language models rely on large-scale visio-linguistic pretraining for obtaining good performance on a variety of downstream tasks. Generally, such models are often either cross-modal (contrastive) or multi-modal (with earlier fusion) but not both; and they often only target specific modalities or tasks. A promising direction would be to use a single holistic universal model, as a "foundation", that targets all modalities at once -- a true vision and language foundation model should be good at vision tasks, language tasks, and cross- and multi-modal vision and language tasks. We introduce FLAVA as such a model and demonstrate impressive performance on a wide range of 35 tasks spanning these target modalities.* This model was contributed by [aps](https://huggingface.co/aps). The original code can be found [here](https://github.com/facebookresearch/multimodal/tree/main/examples/flava). ## FlavaConfig [[autodoc]] FlavaConfig ## FlavaTextConfig [[autodoc]] FlavaTextConfig ## FlavaImageConfig [[autodoc]] FlavaImageConfig ## FlavaMultimodalConfig [[autodoc]] FlavaMultimodalConfig ## FlavaImageCodebookConfig [[autodoc]] FlavaImageCodebookConfig ## FlavaProcessor [[autodoc]] FlavaProcessor ## FlavaFeatureExtractor [[autodoc]] FlavaFeatureExtractor ## FlavaImageProcessor [[autodoc]] FlavaImageProcessor - preprocess ## FlavaImageProcessorFast [[autodoc]] FlavaImageProcessorFast - preprocess ## FlavaForPreTraining [[autodoc]] FlavaForPreTraining - forward ## FlavaModel [[autodoc]] FlavaModel - forward - get_text_features - get_image_features ## FlavaImageCodebook [[autodoc]] FlavaImageCodebook - forward - get_codebook_indices - get_codebook_probs ## FlavaTextModel [[autodoc]] FlavaTextModel - forward ## FlavaImageModel [[autodoc]] FlavaImageModel - forward ## FlavaMultimodalModel [[autodoc]] FlavaMultimodalModel - forward