Automate instalation of dependencies in notebook.

Add a note in README about running in docker too to reduce cruft on your
host box.

Good luck, be nice!

README.md

@@ -10,6 +10,35 @@ To clone or edit an unseen voice, VoiceCraft needs only a few seconds of referen
 ## News
 :star: 03/28/2024: Model weights are up on HuggingFace🤗 [here](https://huggingface.co/pyp1/VoiceCraft/tree/main)!
 
+## QuickStart
+For Linux only, or likely Windows Subsystem for Linux (WSL) ubuntu.
+```bash
+# 1. clone the repo on in a directory on a drive with plenty of free space
+git clone git@github.com:jasonppy/VoiceCraft.git
+cd VoiceCraft
+
+# 2. assumes you have docker installed with nvidia container container-toolkit
+# https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/1.13.5/install-guide.html
+# sudo apt-get install -y nvidia-container-toolkit-base || yay -Syu nvidia-container-toolkit || echo etc...
+
+# 3. Try to start an existing container otherwise create a new one passing in all GPUs
+./start-jupyter.sh
+
+# 4. now open a webpage on the host box to the URL shown at the bottom of:
+docker logs jupyter
+
+# 5. optionally look inside from another terminal
+docker exec -it jupyter /bin/bash
+export USER=(your_linux_username_used_above)
+export HOME=/home/$USER
+sudo apt-get update
+
+# 6. confirm video card(s) are visible inside container
+nvidia-smi
+
+# 7. Now in browser, open inference_tts.ipynb and work through one cell at a time
+echo GOOD LUCK AND BE NICE
+```
 
 ## TODO
 The TODOs left will be completed by the end of March 2024.

start-jupyter.sh

@@ -0,0 +1,21 @@
+#!/usr/bin/env bash
+## Assumes you have docker installed with nvidia container container-toolkit
+# https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/1.13.5/install-guide.html
+# sudo apt-get install -y nvidia-container-toolkit-base || yay -Syu nvidia-container-toolkit || echo etc...
+## Try to start an existing container otherwise create a new one
+docker start jupyter 2> /dev/null || \
+docker run -it \
+    -d \
+    --gpus all \
+    -p 8888:8888 \
+    --name jupyter \
+    --user root \
+    -e NB_USER="$USER" \
+    -e CHOWN_HOME=yes \
+    -e GRANT_SUDO=yes \
+    -w "/home/${NB_USER}" \
+    -v "$PWD":"/home/$USER/work" \
+    jupyter/base-notebook
+
+## `docker logs jupyter` to get the URL link and token e.g.
+## http://127.0.0.1:8888/lab?token=blahblahblahblabhlaabhalbhalbhal