# FLAVA

## Overview

The FLAVA model was proposed in [FLAVA: A Foundational Language And Vision Alignment Model](https://arxiv.org/abs/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

## 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