---
license: cc-by-nc-nd-4.0
pipeline_tag: image-segmentation
tags:
- one-shot anomaly-detection
- industrial-inspection
- meta-learning
- pytorch
library_name: pytorch
language:
- en
base_model:
- google/efficientnet-b4
---

# MetaUAS Model Weights

This repository contains pre-trained weights for the MetaUAS anomaly detection model. This repository contains the paper described in [MetaUAS: Universal Anomaly Segmentation with One-Prompt Meta-Learning](https://huggingface.co/papers/2505.09265)


## Model Files

| File | Description | Size |
|------|-------------|------|
| `metauas-256.ckpt` | MetaUAS model (256x256 resolution) | ~85MB |
| `metauas-512.ckpt` | MetaUAS model (512x512 resolution) | ~85MB |

## Usage

```python
from huggingface_hub import hf_hub_download

# Download a specific file （"metauas-256.ckpt"） from a Hugging Face repository

file_path = hf_hub_download(
    repo_id="csgaobb/MetaUAS", 
    filename="metauas-256.ckpt",
    repo_type="model"  # Optional: defaults to "model"
)

# Output the local cache path where the file is stored
print(f"File successfully downloaded to: {file_path}")

```

## License

cc-by-nc-nd-4.0