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Usage

cassian up [options]
Reads cassian.yaml, picks the best available node, starts your container, and restores your workspace. If an instance with the same name is already running, it stops it first.

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Options

FlagDescription
--gpu <type>Override GPU type from cassian.yaml (e.g. l4, a10g)
--no-syncSkip pushing local files after the instance starts
--no-setupSkip workspace.setup and auto-detected dependency install

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What happens

  1. Validates your cassian.yaml (including GPU type check)
  2. Connects to Cassian and provisions a container
  3. Restores your workspace files from the last session
  4. Prints runtime info (Python version, Torch version, GPU model)
  5. Installs dependencies (auto-detected or from workspace.setup)
  6. Shows connection instructions

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Startup time

First cassian up for a new volume takes 30 to 60 seconds depending on how much data is in your workspace. Repeat cassian up (after cassian down) is faster because your volume is cached on the node. Typically under 20 seconds.

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Switching GPUs without editing cassian.yaml

cassian up --gpu l4
cassian up --gpu a10g
Useful when your preferred type is unavailable. The flag overrides gpu.type for this session only — your cassian.yaml is unchanged.

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Fast restart

cassian up --no-sync --no-setup
Skips both the file push and the setup command. Use when your environment is already installed and your files haven’t changed — shaves 30+ seconds off restarts.

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Auto dependency install

If workspace.setup is not set in cassian.yaml, Cassian detects and installs automatically:
  • requirements.txt in project root runs pip install -r requirements.txt
  • pyproject.toml in project root runs pip install -e .
To disable this: cassian up --no-setup To set an explicit command: 
workspace:
  setup: "pip install -r requirements.txt && python setup_data.py"

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GPU type validation

x Unknown GPU type 'rtx-3090'.
  Did you mean: rtx3090?

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Runtime banner

  Python      3.11.9
  Torch       2.6.0+cu124
  GPU         NVIDIA GeForce RTX 3090
  Image       default