---
title: efficientnet-b2.advprop
canonical_url: "https://www.modelscope.cn/models/smp-hub/efficientnet-b2.advprop"
md_url: "https://www.modelscope.cn/models/smp-hub/efficientnet-b2.advprop.md"
repository: smp-hub/efficientnet-b2.advprop
last_updated: 2025-10-21
license: other
pipeline_tag: image-classification
tasks:
  - image-classification
parameters: 9.2M
tensor_type:
  - F32
  - I64
library_name:
  - safetensors
  - pytorch
frameworks:
  - pytorch
downloads: 81
stars: 0
tags:
  - segmentation-models-pytorch
  - image-classification
  - pytorch
  - efficientnet
---

# efficientnet-b2.advprop

> efficientnet-b2.advprop - smp-hub 在 ModelScope 开源的模型。Model card for efficientnet-b2.

smp-hub/efficientnet-b2.advprop 是 ModelScope 魔搭社区上的 9.2M 参数image-classification模型，采用 other 许可。

- **Repository**: smp-hub/efficientnet-b2.advprop
- **License**: other
- **Tasks**: image-classification
- **Parameters**: 9.2M
- **Tags**: segmentation-models-pytorch, image-classification, pytorch, efficientnet
- **Downloads**: 81
- **Stars**: 0
- **Last updated**: 2025-10-21

Source: https://www.modelscope.cn/models/smp-hub/efficientnet-b2.advprop

---

# Model card for efficientnet-b2.

This repository contains the `advprop` pre-trained weights for the `efficientnet-b2` model used as 
encoder in the [segmentation-models-pytorch](https://github.com/qubvel-org/segmentation_models.pytorch) library.

### Example usage:

1. Install the library:

```bash
pip install segmentation-models-pytorch
```

2. Use the encoder in your code:

```python
import segmentation_models_pytorch as smp

model = smp.Unet("efficientnet-b2", encoder_weights="advprop")
```

### References

- Github: https://github.com/qubvel/segmentation_models.pytorch
- Docs: https://smp.readthedocs.io/en/latest/
- Original weights URL: https://github.com/lukemelas/EfficientNet-PyTorch/releases/download/1.0/adv-efficientnet-b2-6e9d97e5.pth