Hey! Our primary objective for now is to provide the open source community with cool and useful tooling - we found closed source to be much more popular because of better tooling!
Thanks! How do you earn or keep yourself afloat? I really like what you guys are doing. And similar orgs. I am personally doing the same, full-time. But I am worried when I will run out of personal savings.
Uv helps you up though. Use a pyproject.toml and uv sync. Everything will be put into the venv only, nothing spread across the whole system.
The pyproject.toml can even handles build env for you, so you no longer need a setup.sh that installs 10 tool in specific order with specific flag to produce working environment. A single uv sync, and the job is done.
Plus the result is reproducible, so if this time uv sync work, then it also work next time.
Highly recommend if you are still on pip.
Note: Take a example that I used to install unsloth with rocm setup that based on unreleased git version dependencies and graphic card specific build flag, all of them can be handled with one command 'uv sync'. This will require a big pile of shell script if doing another way. https://github.com/unslothai/unsloth/issues/4280#issuecommen...
I recommend installing uv first, then you can install any Python code you want inside a virtual environment to keep it isolated from the rest of the system.
Yep uv pip install unsloth works as well - we probably should have just made that the default - in fact Unsloth makes its own venv using UV if you have it dynamically
I think the website should probably mention those installation preset in unsloth pyproject.toml though. The website instruct you to install dependencies separately. But it turns out there are dedicated preset that install specific rocm/cuda/xpu version in the project.
You would be surprised - we're the 4th largest independent distributor of LLMs in the world - and nearly every Fortune 500 company has utilized either our RL fine-tuning package or used our quants and models - we for example collab directly with large labs to release models with bug fixes.
You would be surprised! Nearly every Fortune 500 company has utilized either our RL fine-tuning package or used our quants and models - the UI was primarily a culmination of pain points folks had when doing either training or inference!
We're complimentary to LM Studio - they have a great tool as well!
Actually the opposite haha- more than 50% of our audience comes from large organizations eg Meta, NASA, the UN, Walmart, Spotify, AWS, Google, and the list goes on!
Unsloth is the real thing. Highly recommended for those running their own AI engines and that want to get the most out of them.
Apache license. Can’t wait to try it out at work! LMStudio’s proprietary license makes getting permission hard.
Some of it is Apache
Some of unsloth studio’s code is Apache? Or some of lmstudio is?
What is unsloths business/income? They seem to be publishing lot of stuff for free, with no clear product to back them?
Hey! Our primary objective for now is to provide the open source community with cool and useful tooling - we found closed source to be much more popular because of better tooling!
We have much much in the pipeline!!
Thanks! How do you earn or keep yourself afloat? I really like what you guys are doing. And similar orgs. I am personally doing the same, full-time. But I am worried when I will run out of personal savings.
that doesnt sound reassuring?
You didn't answer the parent question.
Will check back when there's AMD support.
Tried to build from source on MacOS, but got this error:
Hey will check ASAP and fix - sorry about that
FYI, if any devs are around, the privacy policy still links to the gitbook.
Oh will check and fix - thanks
Installing with pip on macOS is just not an acceptable option. It'll mess up your system just like npm or gem.
This needs to go on homebrew or be a zip file with an app for manual download.
Agree with you, a slightly more maintainable way to use it now is with "uv" or mise. i've used `uv tool install unsloth` for this one.
Yep - uv is a better fit - and you get parallel downloads as well
Hey we're still working on making installation much better - appreciate the feedback!
We come from Python land mainly so packaging and distribution is all very new to us - homebrew will definitely be next!
Uv helps you up though. Use a pyproject.toml and uv sync. Everything will be put into the venv only, nothing spread across the whole system.
The pyproject.toml can even handles build env for you, so you no longer need a setup.sh that installs 10 tool in specific order with specific flag to produce working environment. A single uv sync, and the job is done.
Plus the result is reproducible, so if this time uv sync work, then it also work next time.
Highly recommend if you are still on pip.
Note: Take a example that I used to install unsloth with rocm setup that based on unreleased git version dependencies and graphic card specific build flag, all of them can be handled with one command 'uv sync'. This will require a big pile of shell script if doing another way. https://github.com/unslothai/unsloth/issues/4280#issuecommen...
I recommend installing uv first, then you can install any Python code you want inside a virtual environment to keep it isolated from the rest of the system.
Yep uv pip install unsloth works as well - we probably should have just made that the default - in fact Unsloth makes its own venv using UV if you have it dynamically
I think the website should probably mention those installation preset in unsloth pyproject.toml though. The website instruct you to install dependencies separately. But it turns out there are dedicated preset that install specific rocm/cuda/xpu version in the project.
Would pipx solve the problem?
https://pipx.pypa.io/stable/installation/
Agreed, feels like a vibe-coded frontend based on already given backend features.
Also, never saw any Unsloth related software in production to this day. Feels strongly like a non-essential tool for hobby LLM wizards.
You would be surprised - we're the 4th largest independent distributor of LLMs in the world - and nearly every Fortune 500 company has utilized either our RL fine-tuning package or used our quants and models - we for example collab directly with large labs to release models with bug fixes.
Unsloth is providing the best and most reliable libraries for finetuning LLMs. We've used it for production use-cases where I work, definitely solid.
Glad it was helpful!
Even a brief reading of their site would have spared you this embarrassment.
I know the whole package system across most languages is a dumpster fire but for Python, uv solves a lot of problems.
uv init
uv add unsloth
uv run main.py % or whatever
Yep UV is fantastic - should have just that default!
On my linux systems I use venv to not affect system packages, is that not an option for this situation?
This looks really cool. Any chance you'll support pretraining runs as well?
Nice! Is there something planned to run the finetuning via hf jobs or runpod?
The GUI for the fine tuning looks interesting. Hopefully this leads to a lot of new custom models
Thank you! We're still iterating on it so any suggestions are welcome!
wish there were an option to disable the annoying startup messages with emojis when using the library.
Excited to use this been using unsloth models for the past couple years
Thank you for your continued support - we have much more planned for it!
Can Unsloth Studio use already downloaded models?
IDK how it did but it detected my LM studio downloaded models I have on a spinning drive (they're not in the default location).
Who's the intended user for this?
Is it like, for AI hobbyists? I.e. I have a 4090 at home and want to fine-tune models?
Is it a competitor to LMStudio?
You would be surprised! Nearly every Fortune 500 company has utilized either our RL fine-tuning package or used our quants and models - the UI was primarily a culmination of pain points folks had when doing either training or inference!
We're complimentary to LM Studio - they have a great tool as well!
I don’t know why this is being downvoted. Danielhanchen is legit, and unsloth was early to the fine-tuning on a budget party.
Haha no worries at all :)
From the homepage looks like it: “Training: Works on NVIDIA GPUs: RTX 30, 40, 50, Blackwell, DGX Spark/Station etc.”
you just answered your own question, "AI hobbyists who has 4090 at home". And they are pretty much targeted user of Unsloth since the start.
Actually the opposite haha- more than 50% of our audience comes from large organizations eg Meta, NASA, the UN, Walmart, Spotify, AWS, Google, and the list goes on!
I am unaware lm studio is being used for fine tuning. I believe it only does inference.
Happy to see unsloth making it even easier for people like me to get going with fine tuning. Not that I am unable to I'm just lazy.
Fine tuning with a UI is definitely targeted towards hobbyists. Sadly I'll have to wait for AMD ROCm support.
Thanks! We do have normal AMD support for Unsloth but yes the UI doesn't support it just yet! Will keep you posted!
[dead]
[dead]