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license: apache-2.0
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---
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license: apache-2.0
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language:
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- en
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pipeline_tag: image-to-image
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---
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# Model Card for Model ID
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VIT-MAE-r is a fine-tuned version of MAE for image reconstuction. We release a version fine-tuned from [MAE-Large](https://huggingface.co/facebook/vit-mae-large)
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## Model Details
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VIT-MAE-r is already converted to hf format and should be able to be used directly by `from_pretrained` method.
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### Model Sources
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<!-- Provide the basic links for the model. -->
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [LM4LV: A Frozen Large Language Model for Low-level Vision Tasks](https://arxiv.org/abs/2405.15734v1)
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- **source model**: [MAE-Large](https://huggingface.co/facebook/vit-mae-large)
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## How to Get Started with the Model
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Use the code below to get started with the model.
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``python
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from transformers import AutoImageProcessor, AutoModelForPreTraining
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model = AutoModelForPreTraining.from_pretrained("bytetriper/vit-mae-r")
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``
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## Evaluation
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This model achieves a rFID on ImageNet val set of 1.24, evaluated using the standard tensorflow tool provided by [Guided-Diffusion](https://github.com/openai/guided-diffusion/tree/main/evaluations)
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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@article{zheng2024lm4lv,
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title={LM4LV: A Frozen Large Language Model for Low-level Vision Tasks},
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author={Zheng, Boyang and Gu, Jinjin and Li, Shijun and Dong, Chao},
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journal={arXiv preprint arXiv:2405.15734},
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year={2024}
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}
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## Model Card Authors [optional]
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Boyang Zheng
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## Model Card Contact
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