| --- |
| license: mit |
| datasets: |
| - flwrlabs/celeba |
| metrics: |
| - accuracy |
| base_model: |
| - microsoft/resnet-18 |
| --- |
| # Breaking DataMix – Pretrained Models |
|
|
| This repository provides pretrained models used in our study on inversion attacks against DataMix. |
|
|
| ## Overview |
|
|
| The models are based on a ResNet-18 architecture and are trained on a mixed version of the CelebA dataset. |
| They are specifically designed for evaluating privacy vulnerabilities and recovering private mixing coefficients via inversion attacks. |
|
|
| For full details about the methodology, training setup, and data preprocessing, please refer to the main project repository: |
|
|
| 👉 https://github.com/hehteram/Breaking-DataMix |
|
|
| ## Contents |
|
|
| * Pretrained model checkpoints (.pth) |
| * Variants corresponding to different experimental settings |
|
|
| ## Usage |
|
|
| ```python |
| from huggingface_hub import hf_hub_download |
| import torch |
| |
| path = hf_hub_download( |
| repo_id="hehteram/Breaking-DataMix", |
| filename="models/model.pth" |
| ) |
| |
| model.load_state_dict(torch.load(path)) |
| ``` |
|
|
| ## Notes |
|
|
| * These models are provided for research and reproducibility purposes only. |
| * The dataset used is derived from CelebA with specific modifications (see project repository for details). |
|
|
| ## License |
|
|
| Please refer to the main GitHub repository for licensing and usage terms. |
