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Use HF papers (#38184)

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* Use hf papers

* Hugging Face papers

* doi to hf papers

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Quentin Gallouédec
2025-06-13 13:07:09 +02:00
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## Overview
The GIT model was proposed in [GIT: A Generative Image-to-text Transformer for Vision and Language](https://arxiv.org/abs/2205.14100) by
The GIT model was proposed in [GIT: A Generative Image-to-text Transformer for Vision and Language](https://huggingface.co/papers/2205.14100) by
Jianfeng Wang, Zhengyuan Yang, Xiaowei Hu, Linjie Li, Kevin Lin, Zhe Gan, Zicheng Liu, Ce Liu, Lijuan Wang. GIT is a decoder-only Transformer
that leverages [CLIP](clip)'s vision encoder to condition the model on vision inputs besides text. The model obtains state-of-the-art results on
image captioning and visual question answering benchmarks.
@@ -34,7 +34,7 @@ The abstract from the paper is the following:
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/git_architecture.jpg"
alt="drawing" width="600"/>
<small> GIT architecture. Taken from the <a href="https://arxiv.org/abs/2205.14100" target="_blank">original paper</a>. </small>
<small> GIT architecture. Taken from the <a href="https://huggingface.co/papers/2205.14100" target="_blank">original paper</a>. </small>
This model was contributed by [nielsr](https://huggingface.co/nielsr).
The original code can be found [here](https://github.com/microsoft/GenerativeImage2Text).