Create README.md

README.md

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+---
+license: apache-2.0
+tags:
+- vision
+---
+
+# Vision Transformer (large-sized model) trained using DINOv2
+
+Vision Transformer (ViT) model trained using the DINOv2 method. It was introduced in the paper [ViTMatte: Boosting Image Matting with Pretrained Plain Vision Transformers](https://arxiv.org/abs/2305.15272) by Yao et al. and first released in [this repository](https://github.com/hustvl/ViTMatte). 
+
+Disclaimer: The team releasing ViTMatte did not write a model card for this model so this model card has been written by the Hugging Face team.
+
+## Model description
+
+ViTMatte is a simple approach to image matting, the task of accurately estimating the foreground object in an image. The model consists of a Vision Transformer (ViT) with a lightweight head on top.
+
+## Intended uses & limitations
+
+You can use the raw model for image matting. See the [model hub](https://huggingface.co/models?search=vitmatte) to look for other
+fine-tuned versions that may interest you.
+
+### How to use
+
+We refer to the [docs](https://huggingface.co/docs/transformers/main/en/model_doc/vitmatte#transformers.VitMatteForImageMatting.forward.example).
+
+### BibTeX entry and citation info
+
+```bibtex
+@misc{yao2023vitmatte,
+      title={ViTMatte: Boosting Image Matting with Pretrained Plain Vision Transformers}, 
+      author={Jingfeng Yao and Xinggang Wang and Shusheng Yang and Baoyuan Wang},
+      year={2023},
+      eprint={2305.15272},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV}
+}
+```