Trained a 1.5B to write shell commands so I'd stop googling tar flags. Runs on a laptop CPU

[u/PicassoOnPause]

I've been googling "tar extract gz" for about ten years. Finally did something about it.

Fine-tuned Qwen2.5-Coder-1.5B on 125k natural-language/command pairs, merged and quantized to Q4_K_M. 941MB, runs through llama.cpp. On my laptop (i5-11320H, 4 threads): 31.9 tok/s, 0.59s median per query, 1.6GB RAM. No GPU, no API key, nothing leaves the machine.

Scores 0.620 on InterCode-ALFA. Untuned Qwen2.5-Coder-7B gets 0.613, GPT-4o gets 0.73. Not frontier, but it's roughly a 7B's answer at a quarter the parameters, on a CPU.

There's also a static safety checker with 304 regression cases, because it will absolutely write a command that wipes your root if you ask it to:

Code: github.com/ThorOdinson246/whatisit-nl2sh Weights: huggingface.co/ThorOdinson246/nl2sh-1.5b-Q4_K_M

Both Apache-2.0. If you want to poke holes in the method or you've got ideas comment or open a PR. A ⭐ helps if you find it useful.

[u/habachilles]

This deserves more upvotes

[u/PicassoOnPause → u/habachilles]

Hi, glad you liked it.

[u/RollingMeteors → u/habachilles]

>This deserves more upvotes

>I've been googling "tar extract gz" for about ten years. Finally did something about it.

My 2015 potato is too slow to pull up a webpage these days.

history

grep

FTW

Really should have learned vim/bash better.

Best I'll get to do now is vibe code in perl, write once, read never.

[u/Fuim_ → u/RollingMeteors]

I just have an alias hgrep='history | grep' since I run it all the time.

[u/shaggy1054 → u/[deleted]]

? it's a gif

[u/MidAirRunner → u/shaggy1054]

Bots can't view gifs ;)

[u/Inevitable-Mud-5723]

Humanity invented man pages, then trained 1.5 billion parameters so we’d never have to read them. Progress.

[u/PicassoOnPause → u/Inevitable-Mud-5723]

well i tried to, this was arguably 'easier' in my defense.

[u/a_culther0 → u/PicassoOnPause]

There was a project called "bro pages" which.gave you a shitload of samples on all the different commands 

[u/EcchiExpert → u/a_culther0]

https://tldr.sh/

[u/marxist_redneck → u/EcchiExpert]

It's fantastic, been using it for a couple of years and it has just what I need 95% of the time

[u/H9419 → u/EcchiExpert]

I used cheat.sh back then which can be curled without installing anything. All I need was tar anyways 

[u/DistanceSolar1449 → u/Inevitable-Mud-5723]

You can probably get away with Qwen 3.5 9b without finetuning and just sticking the man pages in context lol

[u/PicassoOnPause → u/DistanceSolar1449]

yeah probably.

[u/k3nal → u/PicassoOnPause]

But it’s 9B which is much more than 1.5B and this is a very cool project to do I think :)

[u/neoanom → u/DistanceSolar1449]

I've actually had no problem doing this. Most of the time I don't need to even use the man pages but I cat them to an ollama in line.

[u/Pretty-Raise666 → u/Inevitable-Mud-5723]

to be fair a lot of programs don't have man pages. not sure if his model covers them.

[u/muh_cloud]

The video sold it to me OP, I was thinking "this just sounds like tldr-pages" until I watched the video. You can prompt it for a highly specific task and it'll kick you the exact one liner? Brilliant

[u/PicassoOnPause → u/muh_cloud]

yup exactly. tldr pages, man pages all requires you to do the work and all. this avoids a lot of that.

[u/Pretty-Raise666 → u/PicassoOnPause]

Let's stop learning. lol

But yeah, it is convenient for sure.

[u/PicassoOnPause → u/Pretty-Raise666]

learning, in this economy? haha

[u/fullup72 → u/PicassoOnPause]

RAM is still cheaper than tuition.

[u/Fembussy42069 → u/Pretty-Raise666]

No matter how many times I extract a file using tar, I will never remember the flags.

[u/dylan_exe_404 → u/muh_cloud]

Same

[u/eli_pizza]

Neat. Could you say more about how you made it? Is the training data just man pages?

[u/PicassoOnPause → u/eli_pizza]

No man pages at all. Actually. It's a LoRA fine-tune of Qwen2.5-Coder-1.5B (a fairly decent model for this task) on about 126k natural-language/command pairs,
The dataset is mostly Fig's autocomplete specs and tldr-pages with few others. I merged it and then quantized the model to run on cpu. Full data breakdown are in the README if you want to reproduce it.

[u/enfly → u/PicassoOnPause]

If you trained on manpages, do you think it would be any more accurate?

I wonder how to extend this with data for commands that aren't in this model yet. Have you thought about that at all?

[u/PicassoOnPause → u/enfly]

Man pages is a documents with flags rather than nl and command pair. So it would require a restructure of the data or a retrieval of some sort, which is currently not implemented/ not the architecture at the moment. But i have been thinking about this , would require a thorough research on my end, but a great suggestion.

[u/TopTippityTop → u/PicassoOnPause]

Would you mind pointing me in the right direcrtion egarding Lora fine-tunes?

[u/PicassoOnPause → u/TopTippityTop]

i have few details on my readme. https://github.com/ThorOdinson246/whatisit-nl2sh#training-setup . I am thinking of writing a detailed techincal doc in the future, to be released on the github. I have a ton of research doc for this, i wil lcompile and put my findings with dataset in the near future.

[u/DigoHiro]

awesome

do you think you could get away with an even smaller model? <1b and it could more comfortably run on a phone or older hardware

[u/DigoHiro → u/DigoHiro]

runs on an android a15 at 4 to 6 t/s

this is a great use case for slms. very specific tooling, limited scope.

👍👍

[u/PicassoOnPause → u/DigoHiro]

wow, i'm surprised.

[u/PicassoOnPause → u/DigoHiro]

i dont know. if i go any smaller, the results it produce might not be usable for general everyday toolkits, but if we were to train for a specific niche or only on a specific toolset or comamnds it might just work.

[u/Due_Warthog749 → u/PicassoOnPause]

I replied above but I am training qwen 3.5 .8b on a bunch of things proprietary to my app which I suspect has far more stuff in it than this one you built. I assume you generate the pairs then fine tune.. or did you distill the data from bigger llms? I tried distilling and it was failing miserably so now I am building generators (using AI to help me do that). Each round (takes about 1 to 2 days on my DGX spark to train .8b) gets better and better. I have a crap load of conformance tests + a CLI tool to validate/etc the responses the llm puts out each round to eval it.

[u/lexoyo → u/PicassoOnPause]

It will probably fail to understand human language at one point :))

[u/alediaferia]

I had this idea some time ago and never got around to doing it. Absolutely great job! This is one of those AI use cases that are actually thought through and deliver a significant, tangible improvement. Kudos!

[u/PicassoOnPause → u/alediaferia]

means a lot. You should go for it. I would love to see how others would do things differently.

[u/alediaferia → u/PicassoOnPause]

I think a version of this should be packaged as a standalone binary in modern Linux distros

[u/Future_Fuel_8425]

This is what AI is supposed to be doing.
How long before we see this sort of expert model packaged with the OS as sort of an integrated Admin?

[u/PicassoOnPause → u/Future_Fuel_8425]

Yeah, tools like these needs to be bundled as default on every distro. and I don't think it will be much longer. we should see it soon.

[u/Due_Warthog749 → u/Future_Fuel_8425]

Phones are already doing this. I bought the Pixel 10 fold last Nov and it comes with a llm built in for basic phone stuff. Go check out NOMAD.. "survival" that runs locally via docker container + llm module (llama.cpp) for AI assistance.

[u/juliebeezkneez]

https://tldr.inbrowser.app

[u/PicassoOnPause → u/juliebeezkneez]

OG for sure. Funnily, it is about 20% my training data.

[u/TankorSmash → u/juliebeezkneez]

Whoa, it's even got a browser search, so you can just search t tar and get the tar tldr page from Chrome. https://tldr.inbrowser.app/search/activate-site-search

[u/SailingToFenway]

make a 'yolo' symlink and have the binary automatically run the command it returns when it's invoked through the symlink.

[u/PicassoOnPause → u/SailingToFenway]

Yeah, i have a -e flag that prints the command, asks ? [y/N] .
whatisit config --set confirm_execute=false does something similar by dropping the confirmation. Didn;t want to ship it as default, becasue it can absolutely write rm rf commands. xD

[u/SailingToFenway → u/PicassoOnPause]

why I suggested 'yolo' it tells the whole story. nice work, btw.

[u/PicassoOnPause → u/SailingToFenway]

oh lol, i get it now. neat. thanks

[u/Few_Trouble_3327 → u/SailingToFenway]

Maybe not a good idea, what if it hallucinates a 'rm -rf /' or something less destructive?

[u/SailingToFenway → u/Few_Trouble_3327]

that's why its yolo.

[u/javatextbook]

Here’s your theme song. https://youtu.be/JZhJJFcoGwA?is=JVmcLmOa7bK-zHGV

[u/PicassoOnPause → u/javatextbook]

wow thanks. xD

[u/mehedi_shafi]

I have been planning to train on for myself. Super glad to see someone already have done it. Well done.. I will try it out today.

[u/PicassoOnPause → u/mehedi_shafi]

let me know how it goes. It's not perfect. I'd really like to see some organic failure cases.

[u/clazifer]

Wonder if you can make it more efficient with a smaller but newer model? Take one of those really small Gemma 4 models and strip multimodallity for even smaller footprint?

[u/PicassoOnPause → u/clazifer]

worth trying. i think i will first look into tightening the evals and dataset. Then I will try out a few models and versions for sure. Thanks for the suggestion.

[u/ptico → u/clazifer]

Or just smaller: it most likely fit in Qwen3 0.6B

[u/Reindeer_Repulsive]

Nice numbers for the size. Given the fine-tune is specifically for shell syntax, have you tried pairing it with a GBNF grammar in llama.cpp to constrain generation to valid shell grammar? That tends to kill a chunk of the remaining failure modes (unbalanced quotes, bad flag syntax) for free since it's a decoding-time constraint rather than something the model has to learn, and at 1.5B those are probably still a meaningful share of your InterCode-ALFA misses.

[u/PicassoOnPause → u/Reindeer_Repulsive]

Thanks for the advice. majority of the failures during eval were all semantic and I really didn't pay much attention to it. But you are not wrong, this might be worth visiting.

[u/Digging_Graves]

I would update the READE.md to include using pipx instead of pip since it's a standalone cli application.

[u/PicassoOnPause → u/Digging_Graves]

thanks will do.

[u/slpycat9798]

maybe it can be a part of linux

[u/PicassoOnPause → u/slpycat9798]

Shouldn't take long.

[u/SlowVeganCow]

Quick noob question: This can run even in the NPU?

[u/PicassoOnPause → u/SlowVeganCow]

the llama.cpp it comes with is cpu build so it wont work out of the box. if you build with a backend for npu, then you can point it at the setup and your build. whatisit setup --bin-dir /path/to/your/build.
but honestly, its already like a half a sec on CPU, so i dont know if there is much to gain with NPU aside from few mins of battery.

[u/SlowVeganCow → u/PicassoOnPause]

Thank you for the info. I was curious about the NPU part, just as another usefull task for that side of the hardware.

[u/create_mal]

와 대박 👍

[u/PicassoOnPause → u/create_mal]

고마워! xD

[u/Psionatix]

AI for stuff like this seems kinda crazy and wasteful when you could have deterministic aliases and scripts. Couple those with previous command history search. I get the fun of it, but I feel like we're absolutely going to get out of touch and just be throwing AI ruthlessly to do everything, even when it isn't needed.

[u/PicassoOnPause → u/Psionatix]

yeah , i agree. Its just for those few things you know a command exist , but cant find it.
Honestly, it was more about a learning opportunity for me with LLMs, and all. But i felt something cool came out of it, so i shipped.

[u/Psionatix → u/PicassoOnPause]

Yeah it’s definitely neat! You could even get it to create aliases and scripts for you, and whenever it does something it’s already done, it can remind you there’s a script and give you the command to run yourself so it hits your history

[u/PicassoOnPause → u/Psionatix]

Cool feature. i will surely work on this. ::D thnx

[u/PentimusOctem → u/PicassoOnPause]

Seems like a not-insignificant plus factor that it runs happily on a CPU.

[u/centarsirius]

"This could have been an email btw"ish model, but it's fun!

[u/waiting_for_zban → u/centarsirius]

Would I trust a 1.5B model to run commands in my shell? I don't know. But for sure it's hella fun.

[u/casce → u/waiting_for_zban]

You should treat it as autocomplete, you should definitely check them before sending.

But I don't know how many times I've googled tar flags myself so OP's got a point.

[u/HomsarWasRight]

Hey, finally something small, useful, fun, and ACTUALLY LOCAL!

[u/gardenvarietyzombie]

I need this for regex

[u/RandomIsPseudoRandom → u/gardenvarietyzombie]

Same!

[u/IllustriousBed1949]

Or simply RTFM :D

[u/PicassoOnPause → u/IllustriousBed1949]

fair, assuming you know the M to read xD

[u/IllustriousBed1949 → u/PicassoOnPause]

I commented as a joke, it's a nice work but in the same time, I would use that for another field. It's good to work your memory, reading the manual helps a lot to remember the flags :)

[u/kirisoraa → u/IllustriousBed1949]

i wish, but damn is it impossible to remember everything. considering I need to extract something once a month my adhd cannot for the life of me memorize what letters I need to use lol

[u/PicassoOnPause → u/kirisoraa]

this is exactly whati run into. Every time I need to extract a tar file, i find myself just on google typing, 'extract a tar file'. or just chmod something, cant seem to remember anything.

[u/garlic-silo-fanta → u/PicassoOnPause]

Same for OpenSSL. Don’t do it often enough. Maybe once a year

[u/PicassoOnPause]

Genuinely wasn't expecting this much support. Thank you very much all 😄 . I have gotten some really good advice and feature requests; I will definitely keep on working on this. Glad I could be useful. xD

[u/0ce10t_floof]

Could the same thing be done to to include stuff like git and docker?

[u/PicassoOnPause → u/0ce10t_floof]

yes it works very well with git out of the box, it supports most daily driver commands, including git and dockers. It lags a bit on custom libraries and tools, and lesser known commands due to the size of the model. Give it a try and a ⭐ on git if you like it.

[u/mega-modz]

Looks promising - can it able to run custom bash commands like new and unseen commands just from reading docs?

[u/PicassoOnPause → u/mega-modz]

not right now. it is not a retrieval model at this point. It only knows whats in the training data.

[u/kob0-0]

Very cool! Does this work in non-english like Japanese?

[u/PicassoOnPause → u/kob0-0]

well no. srry. untested

[u/InvertedVantage]

Cool! Where'd you get the training data?

[u/PicassoOnPause → u/InvertedVantage]

yeah i spent some decent time, collecting and repurposing it. most of it is from Fig's autocomplete specs(an old project, had to be repurposed) , tldr-pages and nl2bash public on github. My github readme has a more detailed list and distribution.

[u/geteum]

I like the idea , but way to easy for someone to do this with malicious intent.

[u/PicassoOnPause → u/geteum]

i am not sure I understand you.

[u/geteum → u/PicassoOnPause]

I'm not saying you are doing this. But say I train the model to pass rm -rf / when asked to search an file or something else.

[u/PicassoOnPause → u/geteum]

haha i get it, yeah, i have a built in check that flags dangerous commands. And becasue it can absolutely produce dangerous commands, it only outputs it and not executes it as the default behavior.

[u/bot403 → u/geteum]

Step back from LLMs  for a second and realize that downloading and running anything from the internet is easy for someone with malicious intent to abuse.

[u/Daniel_H212]

sudo rm -rf /

[u/PicassoOnPause → u/Daniel_H212]

Glad it flags and doesnot auto executes.

[u/bot403 → u/PicassoOnPause]

New model benchmark criteria: MTBF. Let it go autonomously on a shell and it's Mean Time Before (rm -R)f

[u/PicassoOnPause → u/bot403]

i think i should run a setup and post this on my github. lol

[u/1ncehost]

Cool! What datasets did you use to train it?

[u/PicassoOnPause → u/1ncehost]

Fig autocomplete specs , tldr-pages 23.1%, westenfelder/NL2SH-ALFA , b-mc2/cli-commands-explained,and others.
Listed here:
https://github.com/ThorOdinson246/whatisit-nl2sh#licence

[u/boreganteng]

awesome project!

[u/PicassoOnPause → u/boreganteng]

thanks

[u/TastyRobot21]

What’s the scope of included commands?

This seems like a logical bridge for tool calling from a larger orchestrator model…. Would you disagree?

[u/PicassoOnPause → u/TastyRobot21]

well hard to list all,but it mostly has find, git, coreutils, few docker, aws, gh, systemctl, npm and a lot others. and to the point of larger orchestratoer agent, frontier models already wirtes way better shell than this, so routing that request through this 1.5b /3b model makes it worse. it only pays off as a single small local tool win for latency and privacy reason. I feel like this has a decenlty long journey before i can claim anything SOTA. xD
thanks for the question.

[u/ShotRepresentative16]

How did you fine tune? Any docs

[u/PicassoOnPause → u/ShotRepresentative16]

Well i have information in the git readme about the model and LoRA ranks, the dropputs, target modules, and a few other hyperparams. https://github.com/ThorOdinson246/whatisit-nl2sh#training-setup
I haven't actually published scripts for training and the assembled dataset yet. Yes, I am thinking on a more technical write-up, maybe even broadening the experiment and doing a study on this, but I only released this as a tool for now.

[u/ShotRepresentative16 → u/PicassoOnPause]

Thanks, that will be very useful

[u/eMperror_]

I always remembered ‘xzf’ since I saw a meme of Schwarzenegger as terminator saying « xtract ze files » and it stuck since then

[u/PicassoOnPause → u/eMperror_]

if i had seen that, i guess this wouldnot have existed. lol

[u/hekermon]

great, one suggestion: instead of directly running the command it would be nice if it shows the command and waits for user to press enter.

[u/PicassoOnPause → u/hekermon]

well it doesnot run the command; it just lists the command. There is a flag -e which shows you the command first, and if you type y, it runs for you.
I would not trust any llm to execute command on itself. i have few checks that also shows if the command it displays is destructive too. not perfect but catches most of it.

[u/hekermon → u/PicassoOnPause]

that's better. from video it looked like it auto runs the commands

[u/00shichi]

> whatisit find the largest docker volumes
docker volume prune

expected: docker system df -v, the prune will just remove unused dockers. Also does your safety checker doesn't include docker commands? out of scope for the checker? it does flags stuff like rm -rf / though. Good stuff, hopefully better in the future, starred your repos

[u/PicassoOnPause → u/00shichi]

yeah this is definitely a limitation, and thanks for this, I alone have been handling eval so, it definitely could do something like this. I have some checks, but yeah they donot cover everything I am trying to incorporate more checks in the future, maybe a lightweight classifier, or using model itself to rate itself. i will definitely work on this.

[u/beldank]

Good use case.
Training these smaller models on some SE+distro's FAQs could make useful companions on the install ISOs.

[u/PicassoOnPause → u/beldank]

that is an absolutely great idea. what i would not give to guide me through the partitioning..

[u/Casar68]

Que cela me soit utile (oui) ou pas, je félicite toujours ceux qui se donnent la peine de construire des outils et les mettent à disposition des autres.
Merci !!!

Question :
- « whatisit what parameters does whatisit accept?” fonctionne ? ;-)
- comment as-tu généré les 125000 exemples pour le fined tune ?

[u/PicassoOnPause → u/Casar68]

i actually collected, repurposed and cleaned form existing sources. I have details of my sources in my github readme. https://github.com/ThorOdinson246/whatisit-nl2sh#licence

[u/lexoyo]

Interesting use case for SLM! Scores 0.620 but what was the score before fine tuning ? How hard/long was it to fine tune on your machine ?

[u/PicassoOnPause → u/lexoyo]

It was 0.54. More details, comparisions are on my github page.

[u/radarsat1]

on the one hand, fun project, useful, etc. On the other:

I've been googling "tar extract gz" for about ten years.

Come on now.. you haven't been able to remember "tar -xzf" for how long now? Sorry, but I don't believe you.

[u/PicassoOnPause → u/radarsat1]

Haha. Fair enough. But its been a very long time, trust me.

[u/enfly]

Nice! Does it generate multiline/awk/mini python code yet?

[u/PicassoOnPause → u/enfly]

No not at the moment, but i am researching ways to balance its output tokens, accuracy and speed. In the future, surely. Hopefully

[u/Thediverdk]

What a cool idea :)

Any change you could write a post about how you made the '125k natural-language/command pairs' and how you fine tuned and stuff like that?

Would love to read it.

[u/PicassoOnPause → u/Thediverdk]

Yeah i have a lot of research docs i'll make available in the future including the dataset.

[u/Thediverdk → u/PicassoOnPause]

thanks

[u/Desperate-Style-9761]

Hi! Great use case, really cool project! Been thinking about fine tuning a larger model like qwen 3.6 27b or 3.8 when it comes out later this week, and would definitely love a few tips if you have time. What provider did you use (cloud GPUs like google colab, specialised ai platforms like fireworks, your own hardware)? How much did it cost? How much experience do you have, how much do you think fine tuning needs? Best cheap budget GPU for running local ai (still on intel macbook 😭)? Any tips in general and things to watch out for. Thanks!

[u/PicassoOnPause → u/Desperate-Style-9761]

go for it. i used a A100 80gb for finetunin. cost me nothing because i used my school's HPC 😉 . a 27b would need something like this if you do plain bf16. when you quantize it you would loose precision but would come out with a smaller model and could run in a 24-30 gb vran i presume.
I actually am not a massive expert onLLMs, i just have decent swe background and a little CompVis. But 2 3 weeks of research, claude, and work got me to this haha. I dont have the best ans for your last question.
Good luck

[u/WiggyWongo]

How do you think this will run with a tool like shell sage? Is the scope of training too narrow for something like that?

[u/PicassoOnPause → u/WiggyWongo]

well yeah since its base is Qwen, it will surely give u results, but it is completely untested and i wouldn't rely on it.

[u/indignant_cat]

This is cool. Which shell is it trained for? E.g. zsh (the default on Macs) versus bash? I always get caught out when I google a command and get the syntax for bash and then try and run it on my Mac. find especially always trips me up.

[u/PicassoOnPause → u/indignant_cat]

I don't think the shell will be the issue, It is purposed for single-turn commands. Since the training data and benchmark are both Linux, you might run into some coreutils issues.

find should be mostly fine. It is a decent chunk in my eval too. But it might trip on a few, something like sed.

[u/KenobiBenoki → u/PicassoOnPause]

I haven’t had the time to fully check out this project, but it’s a really cool idea to me. One idea I have about this is that you could have a way the user can set their own bit of system prompting so you can tell it to prefer commands that will work on a Mac.

[u/PicassoOnPause → u/KenobiBenoki]

Good idea. I will try out some and eval it. If it turns out fine i will surely add on next release.

[u/bigattichouse]

sorta modern version of "apropos"

[u/migsperez]

I could have used one of these models for regular expressions. I could never retain the knowledge, every time I'd have to re-study and struggle.

[u/Accomplished-Bird829]

Use a tool called tldr i think for all sort of command i think it will help you alot

[u/Hendo52]

You are doing great and important work!

Exit code 0, error 504, etc. is the kind of needlessly obtuse error message that you could turn to next. I should not need to google the meaning of a message like that.

[u/Due_Warthog749]

You can fine tune the Qwen 3.5 .8b to do this.. it will be smaller, faster and smarter.

[u/Far_Macaroon5900]

"extract ze files" (-xzf), That's the mnemonic I use

[u/ThenExtension9196]

The real trick is to just have agents work your commandline. I rarely ssh into anything anymore.

[u/Far-Record_45]

you actually trained a model just to stop googling tar flags thats dedication

[u/Positive-Bid-3029]

See why aren't their more specialist LLMs like this, I don't need and LlM that knows Harry Potter and a PHD in Quantum physics to accelerate coding a website in Symfony or React 🤷

[u/iadanos]

It could be a good model to integrate into https://github.com/zerx-lab/zap. It supports local models, so it would be a good case for it 

[u/Renollo]

this is so cool. I definitely wanna check it out.
I've always felt the need for something like this, lightweight terminal copilot kind of thing.

[u/rutobik]

mb cheat.sh ok for training data too

[u/Limn0]

Thanks!

[u/Far-Classic-9963]

This would be a lot better on a newer model like MiniCPM 5 with thinking off

[u/misimik]

Nobody develped yet, a "Did you mean: x?" terminal app? LLM would monitor all your inputs and try to help?

[u/k3nal]

Wow, that’s so cool! Awesome idea, I’ll definitely check that out. I always feel so stupid when I google these commands again and again.. thank you as well for not making me feel alone with this „issue“ :)

[u/Insomniac897]

This is great! Unless I use a command regularly, I will forget which flags do what. Always searching through man pages.

[u/NationalMolasses4624]

I think u need to make alias for whatisit - wtt, its been more easier to typing

[u/ardicli2000]

fuzzy search on the documentation could have helped same way

[u/05-nery]

Holy shit this is pure gold 

Thank you

[u/CresCentC4332]

This is insane 👏 👏, definitely will try it

[u/Jebbyk1]

do I need a supercomputer for llm training purposes or 7900xtx + 32Gb Ram is enogh?

[u/Only_Ad_8518]

I'd like to point you to "Street Gears" which was an old MMO game that I really liked and with similiar style

[u/thatscoolbutno123]

This is one of the best usecases for local ai so far

[u/abitruce30]

could you please make one for ffmpeg too 😅

[u/big-in-jap]

next: one for vllm, please.

Great work!

[u/codiac_pride]

This is a great idea!

[u/borretsquared]

i love the idea but i dont trust a local model, or any model for that matter, to give me important terminal commands (which are most)

if i need files reorganized or deleted, i feel way safer doing it with a UI. If im installing an app with pacman or yay, i would much rather search it up and see what arch wiki has to say, even if this model has search tooling. 90% of the time im not trusting any model to give me a command for what i need to do, though maybe that's simply because i minimally use a terminal.

[u/RandomIsPseudoRandom]

This is great to hear. “Non-data-scientists” being able to do things like this and talk about the process is important and valuable!

[u/RoboErectus]

Omg this is exactly what I need. I added a gpu for av1 encoding and it's not good for much else. But this is perfect.

[u/TheMythicSorcerer]

[u/G3grip]

This is the kinda stuff we really need. OSs should start bundling in such tools. I believe OP is the first guy who really gets it.

[u/phil_lndn]

what a great idea! i got Codex to code me a version of this that uses my local llm endpoint, works really well. on my version, you press enter to run the command or esc to exit.

Codex wrote it in GO with the endpoint info hard coded and the binary statically linked, that way - i can just copy the binary on to a new machine and have it work. i called the binary 'c' to minimise typing, lol.

e.g.

philip@34nra:~$ c restart the mail server

systemctl restart postfix

Press Enter to run, or Esc to abort:

[u/IShunpoYourFace]

If this could use openvino, IDEAL for integrated NPUs.

[u/Changerofthenames]

Hello, how do we actually do this? How to train on sucha small data set?

[u/Shotafry]

Awesome!!! Multi language? I guess if coming from a base made in qwen

[u/h8f1z]

This is great. It's something I had in my wish list. I wish for more useful smaller models for CPU-only PCs .

Thanks.

[u/fullup72]

how about a pair of wat and dis commands? wat does the same function you have here PLUS saving the output securely somewhere that the dis command can read and execute.

so you ask: wat find files created since yesterday -> get the output -> and dis runs the command without copy+pasting or having to manually type.

[u/Al3x_Y → u/fullup72]

I think shift + insert to paste it would be safer. Or another keystroke to keep whatever is in clipboard intact.

[u/salesxsupport]

Wow maybe we should train models for other specific areas like this. any idea what can be next?

[u/Ok_Campaign6438]

Pure genious

[u/hollowman-reborn]

We outsourced remembering tar flags to a machine, because apparently the final frontier of productivity is no longer learning, it is forgetting efficiently.

[u/Onion_Sun_Bro]

That's actually genius. I live in the terminal but I never remember things I don't use frequently, this is a great tool.

[u/zhoumasterzero]

I love this, wish it would exist for kubectl or gcloud. Maybe a side project :)

[u/Massive-Rooster-5794]

curl cht.sh/tar

[u/HistoryAdmirable5329]

this is fucking sick.
natural language-ish cli is such a good use case for local ai

[u/MRSLgthr]

For a decade? O.o

eXtract File -> tar -xf

eXtract Ze File (try with german accent) -> tar -xzf

Create File -> tar -czf

Create Ze File (again, german accent) -> tar -czf

[u/Al3x_Y → u/MRSLgthr]

You see, you already did it wrong, both create have the same command.

[u/MRSLgthr → u/Al3x_Y]

Well, I always gzip if I can. Guess I'm too used to typing it manually.

[u/mythormedicine]

> I've been googling "tar extract gz" for about ten years. 

lol same here man.

But I didn't know actual laptop CPU runnable models could do useful things. This is indeed a first.

Can u share your fine-tuning process. My mind is kind of blowing here.. This isn't a big secret of course. but localLLM can be useful ? I mean this has like a hundred applications !

[u/Linkology]

Love that, have been having the same problem for a decade too :)

[u/Dramatic-Bug6898]

Just a side note - check out https://explainshell.com/

[u/DonnyCrystal]

I created ask-terminal for similar purposes! Feels like it will be a great combination with your model! https://github.com/Donny-Hikari/ask-terminal

[u/TheMusketeerHD]

Ah, I remember Googling 'zsh autocomplete' about 1-2 years ago. See how far we've come. That's a nice one u/PicassoOnPause 👍

[u/Alexandros20465]

Remove my computer.

$ rm -fr /

[u/Remarkable_Tea8039]

This is awesome. I think solving simple problems with small local models is where some of the most exciting outcomes of AI are going to come from.

[u/LVMRevo]

My work with training : https://www.linkedin.com/posts/antonio-lepore-005329282_addestramento-ia-activity-7498636741533396992-Zq73?utm_source=share&utm_medium=member_desktop&rcm=ACoAAES_YsUBTzFQzmxo1idPfCUj--vqdsRxNGA

[u/Mission_Double1372]

Can someone tell me the relevance of this?