| library_name: segmentation-models-pytorch | |
| license: other | |
| pipeline_tag: image-classification | |
| tags: | |
| - segmentation-models-pytorch | |
| - image-classification | |
| - pytorch | |
| - efficientnet | |
| languages: | |
| - python | |
| # Model card for timm-efficientnet-b1. | |
| This repository contains the `noisy-student` pre-trained weights for the `timm-efficientnet-b1` 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("timm-efficientnet-b1", encoder_weights="noisy-student") | |
| ``` | |
| ### References | |
| - Github: https://github.com/qubvel/segmentation_models.pytorch | |
| - Docs: https://smp.readthedocs.io/en/latest/ | |
| - Original weights URL: https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b1_ns-99dd0c41.pth | |