| ---
|
| license: cc-by-nc-4.0
|
| language: en
|
| tags:
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| - vision
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| - image-feature-extraction
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| - sar
|
| - remote-sensing
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| - synthetic-aperture-radar
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| - masked-autoencoder
|
| - model-hub
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| library_name: transformers
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| pipeline_tag: image-feature-extraction
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| datasets:
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| - Wenquandan777/SAR-1M
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| arxiv: 2512.16635
|
| ---
|
|
|
| # SARMAE Transformers Checkpoints
|
|
|
| Official Hugging Face Transformers-format releases of [SARMAE](https://arxiv.org/abs/2512.16635) ViT encoders, converted for native `transformers` inference with `trust_remote_code=True`.
|
|
|
| | Resource | Link |
|
| |----------|------|
|
| | Paper | [2512.16635](https://arxiv.org/abs/2512.16635) |
|
| | Training dataset | [Wenquandan777/SAR-1M](https://huggingface.co/datasets/Wenquandan777/SAR-1M) |
|
| | Legacy PyTorch weights | [Wenquandan777/SARMAE](https://huggingface.co/Wenquandan777/SARMAE) |
|
| | Source code | [GitHub](https://github.com/BiliSakura/SARMAE-transformers) |
|
|
|
| ## Available checkpoints
|
|
|
| | Variant | Backbone | Stage | Hidden | Layers | Heads | Input |
|
| |---------|----------|-------|--------|--------|-------|-------|
|
| | [sarmae-vit-base-patch16-pretrain](https://huggingface.co/BiliSakura/SARMAE-transformers/tree/main/vit-base-patch16-pretrain) | ViT-B | pretrain | 768 | 12 | 12 | 224 |
|
| | [sarmae-vit-large-patch16-pretrain](https://huggingface.co/BiliSakura/SARMAE-transformers/tree/main/vit-large-patch16-pretrain) | ViT-L | pretrain | 1024 | 24 | 16 | 224 |
|
|
|
| ## Installation
|
|
|
| ```bash
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| pip install transformers timm torch torchvision safetensors huggingface_hub
|
| ```
|
|
|
| ## Usage
|
|
|
| Point `transformers.pipeline` or `AutoModel.from_pretrained` at a variant subfolder:
|
|
|
| ```python
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| from transformers import pipeline
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|
|
| pipe = pipeline(
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| task="image-feature-extraction",
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| model="BiliSakura/SARMAE-transformers",
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| revision="main",
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| trust_remote_code=True,
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| model_kwargs={"subfolder": "vit-base-patch16-pretrain"},
|
| )
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| features = pipe(sar_image, pool=True, return_tensors=True)
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| ```
|
|
|
| Or load a variant directly:
|
|
|
| ```python
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| from transformers import AutoModel
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|
|
| model = AutoModel.from_pretrained(
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| "BiliSakura/SARMAE-transformers",
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| subfolder="vit-base-patch16-pretrain",
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| trust_remote_code=True,
|
| )
|
| ```
|
|
|
| Each variant folder is a self-contained model repository with:
|
|
|
| - `config.json` (`auto_map`, `custom_pipelines`)
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| - `model.safetensors`
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| - `preprocessor_config.json`
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| - `modeling_sarmae.py`, `image_processing_sarmae.py`, `pipeline_sarmae.py`
|
|
|
| ## Convert legacy checkpoints locally
|
|
|
| ```bash
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| python scripts/convert_checkpoint.py models/SARMAE_vitb_checkpoint-last
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| python scripts/convert_checkpoint.py models/SARMAE_vitl_checkpoint-last
|
| ```
|
|
|
| ## Upload to this Hub repo
|
|
|
| ```bash
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| python scripts/upload_to_hub.py models/sarmae-vit-base-patch16-pretrain \
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| --path-in-repo vit-base-patch16-pretrain
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| python scripts/upload_to_hub.py models/sarmae-vit-large-patch16-pretrain \
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| --path-in-repo vit-large-patch16-pretrain
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| python scripts/upload_to_hub.py --hub-readme-only
|
| ```
|
|
|
| ## Citation
|
|
|
| ```bibtex
|
| @misc{liu2025sarmaemaskedautoencodersar,
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| title={SARMAE: Masked Autoencoder for SAR Representation Learning},
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| author={Danxu Liu and Di Wang and Hebaixu Wang and Haoyang Chen and Wentao Jiang and Yilin Cheng and Haonan Guo and Wei Cui and Jing Zhang},
|
| year={2025},
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| eprint={2512.16635},
|
| archivePrefix={arXiv},
|
| primaryClass={cs.CV},
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| url={https://arxiv.org/abs/2512.16635},
|
| }
|
| ```
|
|
|
| ## License
|
|
|
| [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/)
|
|
|
