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@@ -302,7 +302,7 @@ $ python3 compress_classifier.py -a resnet20_cifar ../../../data.cifar10 --resum
 The command-line above will save a checkpoint named `quantized_checkpoint.pth.tar` containing the quantized model parameters. See more examples [here](https://github.com/NervanaSystems/distiller/blob/master/examples/quantization/post_train_quant/command_line.md).
 
 ### Explore the sample Jupyter notebooks
-The set of notebooks that come with Distiller is described [here](https://nervanasystems.github.io/distiller/jupyter/index.html#using-the-distiller-notebooks), which also explains the steps to install the Jupyter notebook server.<br>
+The set of notebooks that come with Distiller is described [here](https://nervanasystems.github.io/distiller/jupyter.html#using-the-distiller-notebooks), which also explains the steps to install the Jupyter notebook server.<br>
 After installing and running the server, take a look at the [notebook](https://github.com/NervanaSystems/distiller/blob/master/jupyter/sensitivity_analysis.ipynb) covering pruning sensitivity analysis.
 
 Sensitivity analysis is a long process and this notebook loads CSV files that are the output of several sessions of sensitivity analysis.