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Introducing Unsloth Studio ✨ A new open-source web UI to train and run LLMs. • Run models locally on Mac, Windows, Linux • Train 500+ models 2x faster with 70% less VRAM • Supports GGUF, vision, audio, embedding models • Auto-create datasets from PDF, CSV, DOCX • Self-healing tool... show more

Unsloth AI

102,948 subscribers

1,742,524 Aufrufe • vor 7 Monaten •via X (Twitter)

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35 Kommentare

Profilbild von Unsloth AI

Unsloth AIvor 7 Monaten

Transform PDFs, CSV, DOCX, TXT or any file into a structured synthetic datasets via Unsloth Data Recipes. Build and edit your datasets visually via a graph-node workflow and use them for fine-tuning. Powered by @NVIDIA DataDesigner.

Profilbild von Unsloth AI

Unsloth AIvor 7 Monaten

Unsloth Studio allows LLMs to run code and programs in a sandbox so it can calculate, analyze data, test code, generate files, or verify an answer with actual computation. This makes answers from models more reliable and accurate.

Profilbild von Daniel Han

Daniel Hanvor 7 Monaten

Some screenshots: SVG rendering of a cute sloth

Profilbild von DanTon

DanTonvor 7 Monaten

• Auto-create datasets from PDF, CSV, DOCX Killer feature

Profilbild von Vladyslav Hunt

Vladyslav Huntvor 7 Monaten

six months ago this required a team of ML engineers and a $50k cloud bill. now it runs on your laptop

Profilbild von NVIDIA RTX Spark

NVIDIA RTX Sparkvor 7 Monaten

congrats on launch! this is an awesome tool 🔥

Profilbild von Matthew Berman

Matthew Bermanvor 7 Monaten

Can I use this if I’m SSHing into a machine?

Profilbild von vikiival

vikiivalvor 7 Monaten

congrats on launch, looking forward to MLX support ✨

Profilbild von Ivan Fioravanti

Ivan Fioravantivor 7 Monaten

Amazing tool release! Let me deep dive on it! Thanks!

Profilbild von KHALM

KHALMvor 7 Monaten

Incredible timing! We're currently using Unsloth to fine-tune DeepCoder-14B on a local RTX 5070 Ti. We are building a specialized Terraform AI trained strictly on compiler-verified, multi-region AWS architectures. The memory optimization in Unsloth is the only reason these fits on a consumer GPU. Can't wait to move the pipeline to Studio.

Profilbild von OneManSaas

OneManSaasvor 7 Monaten

holy crap 70% less VRAM is massive - training on my local setup just became actually viable

Profilbild von himanshu

himanshuvor 7 Monaten

my goat @danielhanchen et al cooked here. there is too much ground for anyone to explore their research hacks

Profilbild von Sophia Yang

Sophia Yangvor 7 Monaten

Nice! Congrats!

Profilbild von Brian Cheong

Brian Cheongvor 7 Monaten

The auto-dataset creation from PDFs and CSVs is the part that actually removes a real bottleneck. Most people quit fine-tuning before they start because data prep takes longer than training.

Profilbild von Protovox

Protovoxvor 7 Monaten

70% less VRAM is the number that matters here. most people can't fine-tune because they don't have A100s sitting around. this makes local training actually practical.

Profilbild von Maxime Labonne

Maxime Labonnevor 7 Monaten

Oh that's really cool, I love the built-in data pipeline. Congrats guys!

Profilbild von alexine 🏴‍☠️

alexine 🏴‍☠️vor 7 Monaten

really cool

Profilbild von mrfakename

mrfakenamevor 7 Monaten

Very cool! I noticed there are now both AGPL and Apache licenses in the repo, could you clarify?

Profilbild von Maziyar PANAHI

Maziyar PANAHIvor 7 Monaten

@nisten freaking cool!

Profilbild von AVB

AVBvor 7 Monaten

I love you Unsloth 💙

Profilbild von koop

koopvor 7 Monaten

2x faster training with 70% less VRAM and auto-dataset creation from PDFs? That's not just a better UI — that's removing almost every barrier that kept fine-tuning out of reach for most developers. Really curious how the self-healing tool calling holds up on complex agentic tasks. This could genuinely change who gets to train their own models.

Profilbild von Lewis Menelaws

Lewis Menelawsvor 7 Monaten

You guys are the 🐐

Profilbild von HealthRanger

HealthRangervor 7 Monaten

This is a huge deal. A tool like this has been needed for a long time!

Profilbild von KITE AI

KITE AIvor 7 Monaten

@ClementDelangue Unsloth Studio: now your laptop can train LLMs. Next step: your LLM can hire other LLMs, expense the compute, and file its own tax returns.

Profilbild von Barathwaj Anandan

Barathwaj Anandanvor 7 Monaten

@danielhanchen This is going to be a game changer!! Been waiting for it for a long time. Keep cooking, boys!!

Profilbild von DawidDD

DawidDDvor 7 Monaten

Exactly the tool I need

Profilbild von Taylor Arndt

Taylor Arndtvor 7 Monaten

@LewisMenelaws Thank you for releasing this. I’m gonna have to check this out.

Profilbild von Vito Cappello 🦞

Vito Cappello 🦞vor 7 Monaten

Awesome!! Love you guys continuing to lower the barrier! Thanks for all you put into it!

Profilbild von NotedallaSfera

NotedallaSferavor 7 Monaten

This is the future we need! Thank you !

Profilbild von Eric ⚡️ Building...

Eric ⚡️ Building...vor 7 Monaten

Good work

Profilbild von Vuk Rosić 武克

Vuk Rosić 武克vor 7 Monaten

this is crazyyyyy

Profilbild von xeon

xeonvor 7 Monaten

Always cookin

Profilbild von Artem Andreenko

Artem Andreenkovor 7 Monaten

You guys are the best! Thank you!

Profilbild von Roshan Ramani

Roshan Ramanivor 7 Monaten

2x faster training with 70% less VRAM? That's not optimization, that's straight up wizardry. Finally, a local LLM setup that won't require selling a kidney for GPU memory

Profilbild von oyasumi

oyasumivor 7 Monaten

this is extremely interesting will definitely be checking it out

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