Introducing the Google Colab CLI

Google Developers Blog

Google Developers Blog2026年6月10日

Introducing the Google Colab CLI

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TL;DR · AI Summary

Google 推出 Colab CLI，提供本地终端与远程 Colab 运行时的无缝连接，支持 GPU/TPU 加速、远程执行和模型下载。

Key Takeaways

使用 colab --gpu A100 或 colab --gpu T4 可快速申请高性能 GPU。
通过 colab exec 可在 Colab 运行时直接执行本地 Python 脚本和 ML 管道。
colab download 和 colab log 可用于下载模型和日志文件。

Outline

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§引言
Google 推出 Colab CLI，为开发者和 AI 代理提供零摩擦的远程执行平台。
·核心功能
Colab CLI 提供 GPU/TPU 加速、远程执行、模型下载和交互式访问等功能。
›实际应用案例
通过 Antigravity 代理使用 Colab CLI 对 Gemma 3-1B 模型进行微调。
·Agent 驱动的工作流程
Colab CLI 可被任何具有终端访问权限的代理使用，包含预打包的 Colab 技能文件。
›QLoRA 管道示例
使用 Colab CLI 运行 QLoRA 管道，通过几个命令完成模型微调。

Mindmap

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查看大纲文本（无障碍 / 无 JS 友好）

Google Colab CLI
- 核心功能
  - GPU/TPU 加速
  - 远程执行
  - 模型下载
  - 交互式访问
- 实际应用
  - QLoRA 管道
  - Gemma 3-1B 微调

Highlights

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Colab CLI 提供零摩擦加速器配置，可快速申请 GPU 或 TPU。
— 第 2 段
⬇︎ 下载 PNG 𝕏 分享到 X
通过 colab exec 可在 Colab 运行时直接执行本地 Python 脚本和复杂 ML 管道。
— 第 2 段
⬇︎ 下载 PNG 𝕏 分享到 X
Antigravity 代理使用 Colab CLI 对 Gemma 3-1B 模型进行微调，仅需几个命令即可完成。
— 第 3 段
⬇︎ 下载 PNG 𝕏 分享到 X

#Google Colab#CLI#AI#机器学习

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Introducing the Google Colab CLI

JUNE 5, 2026

Spencer Shumway

Product Manager

Tyler Pirtle

Software Engineer

Seth Troisi

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Today we are announcing the Google Colab Command-Line Interface (CLI), which bridges the gap between your local terminal and remote Colab runtimes, providing a zero-friction execution platform for both developers and AI agents. The Colab CLI offers:

Zero-Friction Accelerator Provisioning: Request high-powered GPUs or TPUs instantly (e.g., colab --gpu A100 or colab --gpu T4 ).

Simple Remote Execution: Run your local Python scripts and complex ML pipelines directly on Colab runtimes using colab exec .

Seamless Artifact Recovery: Easily retrieve models, datasets, and replayable .ipynb logs via colab download and colab log .

Interactive Access: Drop into an interactive environment on your remote Colab runtime with colab repl or colab console .

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Agent-driven workflows in action

Because the Colab CLI integrates seamlessly into standard terminal environments, it can be used by any agent with terminal access. To ensure your AI assistants can hit the ground running, the CLI includes a prepackaged Colab skill file that provides agents with instant, built-in context on exactly how to leverage the CLI. Let's look at a real life example of something a user or agent might try with the Colab CLI.

*Note that while the example below highlights Antigravity agent using Colab CLI as a tool, Colab CLI can easily be used by Claude Code, Codex, and other agents.

Here is how an Agent can use the Colab CLI for a real-world ML workflow:

#### Fine-tuning Gemma 3-1B

The CLI can be used to run a real QLoRA pipeline that runs end-to-end with just a handful of commands. Offload heavy computational lifting to a GPU without typing a single cloud provisioning command by Instructing Antigravity (or your agent of choice) to build a remote fine-tuning job. In this scenario, we ask our agent to use the Colab CLI to fine-tune google/gemma-3-1b-it on a Text-to-SQL dataset to make the model better at writing SQL queries.

The Antigravity prompt: Use the Colab CLI (https://github.com/googlecolab/google-colab-cli) to fine-tune Gemma 3 1B using QLoRA. Provision a Colab T4 GPU instance, install the necessary ML packages (transformers, datasets, peft, trl, etc.), run my local ~ finetune_run .py script remotely, download the resulting safetensors adapter, save the notebook log, and cleanup.

Antigravity executes:

code

$ colab new --gpu T4
$ colab install transformers datasets peft trl bitsandbytes accelerate
$ colab exec -f finetune_run.py
$ colab log --output gemma_finetune_log.ipynb
$ colab stop

Shell

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Antigravity also uses the "colab download" command to download the adapter model, adapter config, tokenizer config, and tokenizer, which can be used to load and run your fine-tuned model locally. Now you have a remotely fine-tuned model ready to serve from your local device!

Try it out now

The Colab CLI makes powerful Colab compute accessible, programmable, and agent-ready. It is lightweight and easily accessible to any terminal-based AI agent. To start using the Colab CLI yourself, head over to the Google Colab CLI GitHub repository for setup instructions.

We are excited to see how this accelerates your development process and look forward to seeing what you and your agents build!

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