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--- |
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license: cc-by-nc-nd-4.0 |
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pipeline_tag: image-segmentation |
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tags: |
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- one-shot anomaly-detection |
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- industrial-inspection |
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- meta-learning |
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- efficientnet |
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- pytorch |
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library_name: pytorch |
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language: |
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- en |
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base_model: |
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- google/efficientnet-b4 |
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--- |
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# MetaUAS Model Weights |
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This repository contains pre-trained MetaUAS weights for one-shot anomaly detection. This repository contains the paper described in [MetaUAS: Universal Anomaly Segmentation with One-Prompt Meta-Learning](https://huggingface.co/papers/2505.09265) |
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## Model Files |
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| File | Description | Size | |
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|------|-------------|------| |
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| `metauas-256.ckpt` | MetaUAS model (256x256 resolution) | 85MB | |
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| `metauas-512.ckpt` | MetaUAS model (512x512 resolution) | 85MB | |
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## Usage |
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```python |
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from huggingface_hub import hf_hub_download |
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# Download model |
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model_path = hf_hub_download( |
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repo_id="your-username/MetaUAS-weights", |
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filename="metauas-256.ckpt" |
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) |
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``` |
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## License |
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cc-by-nc-nd-4.0 |
