typo and lint fixes

Author: RobJY

docs/hpc/08_ml_ai_hpc/02_pytorch_intro.md

@@ -8,7 +8,7 @@ This tutorial uses PyTorch but the steps are similar for TensorFlow. See our [Te
 
 ## Step 1: Activate the Environment
 
-For simplicity we will use a pre-installed Conda environmnet. Run these commands to activate the environment:
+For simplicity we will use a pre-installed Conda environment. Run these commands to activate the environment:
 
 ```bash
 $ ssh <YourNetID>@adroit.princeton.edu
@@ -188,4 +188,4 @@ Next, we focus on scaling the code to multiple GPUs (go to [next section](./03_p
 
 ## How was the Conda environment made?
 
-Your `/home` directory on Adroit probably has a capacity of 9.3 GB. To store Conda environments in another location see [this page](https://researchcomputing.princeton.edu/support/knowledge-base/checkquota). See the Research Computing knowledge base on [PyTorch](https://researchcomputing.princeton.edu/support/knowledge-base/pytorch) for installation directions.
+Your `/home` directory on Adroit probably has a capacity of 9.3 GB. To store Conda environments in another location see [this page](https://researchcomputing.princeton.edu/support/knowledge-base/checkquota). See the Research Computing knowledge base on [PyTorch](https://researchcomputing.princeton.edu/support/knowledge-base/pytorch) for installation directions.