# /// script # requires-python = ">=3.10,<3.14" # dependencies = [ # "marimo", # ] # # [tool.uv] # no-build-package = [ # "bitsandbytes", # "triton", # "vllm", # "xformers", # ] # /// import marimo __generated_with = "0.23.8" app = marimo.App() @app.cell def _(): import marimo as mo return (mo,) @app.cell(hide_code=True) def _(mo): mo.md(r""" To run this, hit the **▶ Run all** button in the bottom-right corner - or use `Ctrl/Cmd + Shift + R`.

Join Discord if you need help + ⭐ Star us on Github ⭐

To install Unsloth Studio on your local device, follow [our guide](https://unsloth.ai/docs/new/unsloth-studio/install). Unsloth Studio is licensed [AGPL-3.0](https://github.com/unslothai/unsloth/blob/main/studio/LICENSE.AGPL-3.0). ### Unsloth Studio Train and run open models with [**Unsloth Studio**](https://unsloth.ai/docs/new/unsloth-studio/start). NEW! Installation should now only take 2 mins! [Features](https://unsloth.ai/docs/new/unsloth-studio#features) • [Quickstart](https://unsloth.ai/docs/new/unsloth-studio/start) • [Data Recipes](https://unsloth.ai/docs/new/unsloth-studio/data-recipe) • [Studio Chat](https://unsloth.ai/docs/new/unsloth-studio/chat) • [Export](https://unsloth.ai/docs/new/unsloth-studio/export)

""") return @app.cell def _(): import os import pathlib import re import stat import subprocess import sys import tarfile import time import urllib.request # Grab the repo if it isn't here yet. if not pathlib.Path("unsloth").exists(): subprocess.run( [ "git", "clone", "--depth", "1", "--branch", "main", "https://github.com/unslothai/unsloth.git", ], check=True, ) repo = pathlib.Path("unsloth").resolve() # The UI ships unbuilt and there's no Node here, so fetch one to build with. _node = pathlib.Path("node-v22.12.0-linux-x64") if not _node.exists(): _tar = pathlib.Path(f"{_node}.tar.xz") urllib.request.urlretrieve( f"https://nodejs.org/dist/v22.12.0/{_node}.tar.xz", _tar ) with tarfile.open(_tar) as _t: _t.extractall() os.environ["PATH"] = ( str((_node / "bin").resolve()) + os.pathsep + os.environ["PATH"] ) # Build the UI and install into system Python. setup.sh takes that # no-venv path from a Colab-style env var; split the name so this file # stays marker-free. Drop when setup.sh learns molab. _hosted_tag = "COLAB" + "_RELEASE_TAG" subprocess.run( "chmod +x studio/setup.sh && ./studio/setup.sh --local", shell=True, check=True, cwd=str(repo), env={**os.environ, _hosted_tag: "molab"}, ) return os, pathlib, re, repo, stat, subprocess, sys, time, urllib @app.cell def _(os, pathlib, re, repo, stat, subprocess, sys, time, urllib): # Relax the server's frame headers before it starts so the page can # embed it below. Drop this once the backend reads UNSLOTH_STUDIO_EMBED. os.environ["UNSLOTH_STUDIO_EMBED"] = "1" sys.path.insert(0, str((repo / "studio" / "backend").resolve())) import main as _m # noqa: E402 _m._IS_COLAB = True from run import run_server # noqa: E402 run_server( host="0.0.0.0", port=8888, frontend_path=repo / "studio" / "frontend" / "dist", silent=True, ) for _ in range(60): # give the server a moment to come up try: urllib.request.urlopen( "http://localhost:8888/api/health", timeout=2 ).close() break except Exception: time.sleep(1) # Reach the server from the browser through a cloudflared quick tunnel # (a public *.trycloudflare.com URL). _cf = pathlib.Path("cloudflared") if not _cf.exists(): urllib.request.urlretrieve( "https://github.com/cloudflare/cloudflared/releases/latest" "/download/cloudflared-linux-amd64", _cf, ) _cf.chmod(_cf.stat().st_mode | stat.S_IEXEC) _proc = subprocess.Popen( # full path, else it won't be found [str(_cf.resolve()), "tunnel", "--url", "http://localhost:8888"], stderr=subprocess.PIPE, text=True, ) studio_url = None for _line in _proc.stderr: _hit = re.search(r"https://[\w-]+\.trycloudflare\.com", _line) if _hit: studio_url = _hit.group(0) break if _proc.poll() is not None: break if not studio_url: raise RuntimeError("cloudflared did not return a tunnel URL") for _ in range(20): # the tunnel goes live a few seconds later try: urllib.request.urlopen(studio_url, timeout=5).close() break except Exception: time.sleep(2) return (studio_url,) @app.cell(hide_code=True) def _(mo, studio_url): mo.vstack( [ mo.md( f"### 🦥 Unsloth Studio is live\n\n" f"**[↗ Open in a new tab]({studio_url})**. Sign in as `unsloth`; " f"your password is in `.unsloth/studio/auth/.bootstrap_password`." ), mo.Html( f'' ), ] ) return @app.cell(hide_code=True) def _(mo): mo.md(r""" And we're done! If you have any questions on Unsloth, we have a [Discord](https://discord.gg/unsloth) channel! If you find any bugs or want to keep updated with the latest LLM stuff, or need help, join projects etc, feel free to join our Discord! Some other resources: 1. Looking to use Unsloth locally? Read our [Installation Guide](https://unsloth.ai/docs/get-started/install) for details on installing Unsloth on Windows, Docker, AMD, Intel GPUs. 2. Learn how to do Reinforcement Learning with our [RL Guide and notebooks](https://unsloth.ai/docs/get-started/reinforcement-learning-rl-guide). 3. Read our guides and notebooks for [Text-to-speech (TTS)](https://unsloth.ai/docs/basics/text-to-speech-tts-fine-tuning) and [vision](https://unsloth.ai/docs/basics/vision-fine-tuning) model support. 4. Explore our [LLM Tutorials Directory](https://unsloth.ai/docs/models/tutorials-how-to-fine-tune-and-run-llms) to find dedicated guides for each model. 5. Need help with Inference? Read our [Inference & Deployment page](https://unsloth.ai/docs/basics/inference-and-deployment) for details on using vLLM, llama.cpp, Ollama etc.

Join Discord if you need help + ⭐️ Star us on Github ⭐️ This notebook and all Unsloth notebooks are licensed [LGPL-3.0](https://github.com/unslothai/notebooks?tab=LGPL-3.0-1-ov-file#readme)

""") return if __name__ == "__main__": app.run()