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.
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
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!
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!
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.
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
On my linux systems I use venv to not affect system packages, is that not an option for this situation?
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!
Tried to build from source on MacOS, but got this error:
Hey will check ASAP and fix - sorry about that
What is unsloths business/income? They seem to be publishing lot of stuff for free, with no clear product to back them?
Can Unsloth Studio use already downloaded models?
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!
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!
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!
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!
From the homepage looks like it: “Training: Works on NVIDIA GPUs: RTX 30, 40, 50, Blackwell, DGX Spark/Station etc.”
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!