transformers/docs/source/en/model_doc/flava.md
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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

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Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com>
2025-03-03 10:33:46 -08:00

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# FLAVA
<div class="flex flex-wrap space-x-1">
<img alt="PyTorch" src="https://img.shields.io/badge/PyTorch-DE3412?style=flat&logo=pytorch&logoColor=white">
</div>
## 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