From 41bbfe814e897de3e2038fb20c8247aef7133e7c Mon Sep 17 00:00:00 2001 From: Chris Date: Fri, 15 Nov 2019 10:39:10 +0100 Subject: [PATCH] default password --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 3f179e7..8fbb537 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,5 @@ # gpu-jupyter -#### Leverage the power of Jupyter and use your NVIDEA GPU and use Tensorflow and Pytorch in collaborative notebooks. +#### Leverage Jupyter Notebooks with the power of your NVIDEA GPU and perform GPU calculations using Tensorflow and Pytorch in collaborative notebooks. ![Jupyterlab Overview](/extra/jupyterlab-overview.png) @@ -30,7 +30,7 @@ As soon as you have access to your GPU locally (it can be tested via a Tensorflo ./start-local.sh ``` -This will run *gpu-jupyter* on the default port [localhost:8888](http://localhost:8888). The general usage is: +This will run *gpu-jupyter* on the default port [localhost:8888](http://localhost:8888) with the default password `asdf`. The general usage is: ```bash ./start-local.sh -p [port] # port must be an integer with 4 or more digits. ``` @@ -111,7 +111,7 @@ where: * port specifies the port on which the service will be available. * and docker-network is the name of the attachable network from the previous step, e.g., here it is **elk_datastack**. -Now, *gpu-jupyter* will be accessable on [localhost:port](http://localhost:8888) and shares the network with the other data-source. I.e, all ports of the data-source will be accessable within *gpu-jupyter*, even if they aren't routed it the source's `docker-compose` file. +Now, *gpu-jupyter* will be accessable on [localhost:port](http://localhost:8888) with the default password `asdf` and shares the network with the other data-source. I.e, all ports of the data-source will be accessable within *gpu-jupyter*, even if they aren't routed it the source's `docker-compose` file. Check if everything works well using: ```bash