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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

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1,742,524 görüntüleme • 7 ay önce •via X (Twitter)

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Unsloth AI profil fotoğrafı

Unsloth AI7 ay önce

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.

Unsloth AI profil fotoğrafı

Unsloth AI7 ay önce

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.

Daniel Han profil fotoğrafı

Daniel Han7 ay önce

Some screenshots: SVG rendering of a cute sloth

DanTon profil fotoğrafı

DanTon7 ay önce

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

Vladyslav Hunt profil fotoğrafı

Vladyslav Hunt7 ay önce

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

NVIDIA RTX Spark profil fotoğrafı

NVIDIA RTX Spark7 ay önce

congrats on launch! this is an awesome tool 🔥

Matthew Berman profil fotoğrafı

Matthew Berman7 ay önce

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

vikiival profil fotoğrafı

vikiival7 ay önce

congrats on launch, looking forward to MLX support ✨

Ivan Fioravanti profil fotoğrafı

Ivan Fioravanti7 ay önce

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

KHALM profil fotoğrafı

KHALM7 ay önce

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.

OneManSaas profil fotoğrafı

OneManSaas7 ay önce

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

himanshu profil fotoğrafı

himanshu7 ay önce

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

Sophia Yang profil fotoğrafı

Sophia Yang7 ay önce

Nice! Congrats!

Brian Cheong profil fotoğrafı

Brian Cheong7 ay önce

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.

Protovox profil fotoğrafı

Protovox7 ay önce

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.

Maxime Labonne profil fotoğrafı

Maxime Labonne7 ay önce

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

alexine 🏴‍☠️ profil fotoğrafı

alexine 🏴‍☠️7 ay önce

really cool

mrfakename profil fotoğrafı

mrfakename7 ay önce

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

Maziyar PANAHI profil fotoğrafı

Maziyar PANAHI7 ay önce

@nisten freaking cool!

AVB profil fotoğrafı

AVB7 ay önce

I love you Unsloth 💙

koop profil fotoğrafı

koop7 ay önce

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.

Lewis Menelaws profil fotoğrafı

Lewis Menelaws7 ay önce

You guys are the 🐐

HealthRanger profil fotoğrafı

HealthRanger7 ay önce

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

KITE AI profil fotoğrafı

KITE AI7 ay önce

@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.

Barathwaj Anandan profil fotoğrafı

Barathwaj Anandan7 ay önce

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

DawidDD profil fotoğrafı

DawidDD7 ay önce

Exactly the tool I need

Taylor Arndt profil fotoğrafı

Taylor Arndt7 ay önce

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

Vito Cappello 🦞 profil fotoğrafı

Vito Cappello 🦞7 ay önce

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

NotedallaSfera profil fotoğrafı

NotedallaSfera7 ay önce

This is the future we need! Thank you !

Eric ⚡️ Building... profil fotoğrafı

Eric ⚡️ Building...7 ay önce

Good work

Vuk Rosić 武克 profil fotoğrafı

Vuk Rosić 武克7 ay önce

this is crazyyyyy

xeon profil fotoğrafı

xeon7 ay önce

Always cookin

Artem Andreenko profil fotoğrafı

Artem Andreenko7 ay önce

You guys are the best! Thank you!

Roshan Ramani profil fotoğrafı

Roshan Ramani7 ay önce

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

oyasumi profil fotoğrafı

oyasumi7 ay önce

this is extremely interesting will definitely be checking it out

Benzer Videolar

finetuning LLMs will never be the same! Unsloth just launched an open-source web UI to run and fine-tune 500+ LLMs without writing any code. key features - 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 calling and code execution - compare models side by side + export to GGUF to get started, I've shared links in the next tweet.

finetuning LLMs will never be the same! Unsloth just launched an open-source web UI to run and fine-tune 500+ LLMs without writing any code. key features - 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 calling and code execution - compare models side by side + export to GGUF to get started, I've shared links in the next tweet.

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Introducing Unsloth Desktop 🦥 The first desktop app to run and train models locally. • Open-source. Runs on Mac, Windows and Linux • Supports MLX, diffusion image/video, audio, GGUF • Connect Claude Code and Codex to local LLMs • 50% more accurate, self-healing tool calls + sandboxed code exec • Works for CPU + multiGPU setups - NVIDIA, AMD, Intel, Mac • Train models 2× faster with 70% less VRAM • Private web search, deep research, RAG, MCP and exports (NVFP4, GGUF) • Use Unsloth’s OpenAI-compatible API and cloud models • Securely deploy LLMs remotely and access anywhere Unsloth Desktop is now available on and GitHub. GitHub: Blog and Guide:

Introducing Unsloth Desktop 🦥 The first desktop app to run and train models locally. • Open-source. Runs on Mac, Windows and Linux • Supports MLX, diffusion image/video, audio, GGUF • Connect Claude Code and Codex to local LLMs • 50% more accurate, self-healing tool calls + sandboxed code exec • Works for CPU + multiGPU setups - NVIDIA, AMD, Intel, Mac • Train models 2× faster with 70% less VRAM • Private web search, deep research, RAG, MCP and exports (NVFP4, GGUF) • Use Unsloth’s OpenAI-compatible API and cloud models • Securely deploy LLMs remotely and access anywhere Unsloth Desktop is now available on and GitHub. GitHub: Blog and Guide:

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You can now fine-tune TTS models with Unsloth! Train, run and save models like Sesame-CSM and OpenAI's Whisper locally with our free notebooks. Unsloth makes TTS training 1.5x faster with 50% less VRAM. GitHub: Docs & Notebooks:

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