dmesg --follow
[ 66541620.000 ] posts.x: @yoheinakajima  |   [ 66512340.000 ] posts.x: Full talk on the RMSNorm paper, the CUDA streams bug, and getting it running in production:  |   [ 66512340.000 ] posts.x: A race condition between two CUDA streams once made a language model repeat itself mid-sentence and lag a step behind its own output. @f_makraduli…  |   [ 66502500.000 ] posts.x: Full talk on why robotics still has no internet-scale dataset, and Skild AI's omnibodied answer to that gap:  |   [ 66502500.000 ] posts.x: A robot that could look at a pattern of stacked blocks and rearrange loose ones to match it, by sight, dates to the 1960s. A teleoperated…  |   [ 66491520.000 ] posts.x: Full talk on how Dyna turned reward models and active learning into a 99.4% success rate on napkin folding:  |   [ 66491520.000 ] posts.x: A robot that succeeds 80 to 90% of the time on a task will string together ten flawless repeats less than 0.1% of the time. @JasonMa2020, CTO and…  |   [ 66436200.000 ] posts.x: Full talk on why Moonlake builds its simulations from causal, code-based object models instead of generated video:  |   [ 66436200.000 ] posts.x: A photorealistic walkthrough of a room and a simulation you can actually act inside of are not the same thing, and mixing them up is the mistake…  |   [ 66427320.000 ] posts.x: Full talk on automating rotational grazing with drones, satellites, and LLMs to get more cattle raised on pasture instead of feedlots:  |   [ 66427320.000 ] posts.x: Rotational grazing could put a lot more cattle back on pasture, but it's bottlenecked by labor: someone has to walk the field every day and decide…  |   [ 66417420.000 ] posts.x: Full talk on building a VLM-labeled, RF-DETR-trained detection pipeline and a toolkit of open vision models for coding agents:  |   [ 66417420.000 ] posts.x: Most vision language models are too slow to run in production, but they can label the dataset that trains the small model that does. @mervenoyann, an…  |   [ 66416280.000 ] posts.x: @HamelHusain That’s a fantastic question! Exploring the humanness of X accounts is a concrete way to determine …  |  
corey@gallon.me:~/til$

Uninstalling Poetry Completions for zsh

FIGURE 1 ⋅ Uninstalling Poetry Completions for zsh

Here’s how to enable: https://python-poetry.org/docs/#enable-tab-completion-for-bash-fish-or-zsh

Uninstalling a specific completion works as follows:

Navigate to `~/.zfunc

❯ cd .zfunc
❯ ll
Permissions Size User     Date Modified Name
.rw-r--r--   243 captivus 31 Aug 10:28  _convert-mp4-to-wav
.rw-r--r--   13k captivus 10 Oct  2023  _poetry
.rw-r--r--   273 captivus 28 Aug 14:20  _stccc-directory-scraper

To uninstall the Zsh completions for _convert-mp4-to-wav, follow these steps:

  1. Remove the Completion File:

Delete the _convert-mp4-to-wav file from your ~/.zfunc directory:

rm ~/.zfunc/_convert-mp4-to-wav
  1. Update the Zsh Completion System:

After removing the file, you should update the Zsh completion system by running the following command:

compinit
  1. Reload Your Zsh Configuration:

Finally, reload your Zsh configuration to ensure that the changes take effect:

source ~/.zshrc

This will remove the completion for _convert-mp4-to-wav from your Zsh setup.

Optionally, you can leave #2 and #3 for later, as the shell should reinitialize compinit when restarted.

corey@gallon.me:~$ tail -f /writing Attach to the stream. An email when I have something worth sending. Replies encouraged!
corey@gallon.me:~$ ls -lt /til ↑2024-09-11 Suppressing Rich Tracebacks in Typer Apps
▸2024-08-31 Uninstalling Poetry Completions for zsh ⋅ you are here
↓2024-08-26 Ubuntu Snaps in WSL & zsh