If anybody is interested: I wrote a little bash and batch script for automating these steps. https://github.com/pxlrbt/move-wsl

Workaround: Create a %UserProfile%\.wslconfig file in Windows and use it to limit memory assigned to WSL2 VM. Example [wsl2] memory=6GB swap=0 localhostForwarding=true This will still consume the entire 6GBs regardless of Linux memory usage, but at least it'll stop growing more than that. Supported settings are documented here.

Assigning more RAM, as suggested in the accepted answer by @sogu, will probably cost you money. You can alternatively solve this problem free-of-charge by assigning swap space instead. This blog post provides a simple few commands to allocate 1G of swap space, which was enough for conda to install most packages in my case: sudo fallocate -l 1G /swapfile sudo chmod 600 /swapfile sudo mkswap /swapfile sudo swapon /swapfile sudo cp /etc/fstab /etc/fstab.bak echo '/swapfile none swap sw 0 0' | sudo tee -a /etc/fstab

Method 1: “The Easy Way” This is my preferred method because it is simple. New environments appear automatically (as long as they have ipykernel installed.) As of the time of this writing, nb_conda_kernels does not yet support Python 3.9. This only affects our base environment which we aren’t going to use for any of our work anyway, right? :). Your other environments can use any Python version including 3.9. Initially, your kernel list (under Change kernel) will only show your current environment. To get your other environment kernels to show automatically: 1. First, install nb_conda_kernels in your base environment. Once this is installed any notebook running from the base environment will automatically show the kernel from any other environment which has ipykernel installed. (base)$ conda install nb_conda_kernels

In ~/.ssh/config, add: Host github.com HostName github.com IdentityFile ~/.ssh/id_rsa_github

Step 1 Open terminal and check cuda version The CUDA version in my system is 12.3. However, in Windows 11, we are unable to install the matching version of the CUDA toolkit. Instead, we will need to install a lower version, such as 12.2. Step 2 Google Cuda toolkit 12.2 and follow the instructions to install Install Success

Problem: In the English version of Windows 10, when displaying Chinese characters, the fonts appear to be incorrect, with some characters appearing larger or smaller, or in odd font styles. Solution For Windows 10 1803 or above Enable UTF-8 language support Control Panel - Region and Language - Region, Non-Unicode (non-Unicode) option.