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@@ -97,6 +97,12 @@ You can train the face reconstruction model by running `train.py`. For example,
 python train.py --path_eg3d_repo <path_eg3d_repo>  --path_eg3d_checkpoint <path_eg3d_checkpoint>       \
                 --FR_system ElasticFace   --FR_loss  ArcFace  --path_ffhq_dataset <path_ffhq_dataset>  \
 ```
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+
+#### Pre-trained models (GaFaR Mapping Network)
+[Checkpoints](https://www.idiap.ch/paper/gafar/static/files/checkpoints.zip) of trained models of the mapping network for whitebox and blackbox attacks are available in the [project page](https://www.idiap.ch/paper/gafar/).
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+
 ### Step 2: Evaluation
 After the model is  trained, you can use it to run evaluation.
 For evaluation, you can use `evaluation_pipeline` script and evaluate on an evaluation dataset (MOBIO/LFW). For example, for evaluation of a face reconstruction of ElasticFace to attack the same system on MOBIO dataset, you can use the following commands: