Volumes are in closed beta for full fine-tuning. Reach out to us to get access.
1Ti) and can grow to 10 TiB (10Ti). They cannot shrink.
Before you start
Install and authenticate the Prime CLI. These commands require Prime CLI 0.9.0 or later. Volumes use the team configured in your CLI. Select a team before creating a volume:Create a volume
Choose a name using lowercase letters, digits, and hyphens:1Ti volume. To choose a different starting size, pass --size:
--cluster <name>; otherwise, the CLI uses your first available cluster.
List volumes
create and list accept --output json (or -o json). JSON includes the volume’s clusterId.
SSH into a volume
Open a session to inspect outputs or stage datasets. Configure your SSH key withprime config set-ssh-key-path <private-key-path> first.
/volume. Bare prime volumes ssh <name> opens a read-write session by default; --read-only (or --read) mounts it read-only to inspect or download files without changing them. Pass --read-write explicitly to upload or edit files:
prime volumes get <name> <remote> [local] or prime volumes put <name> <local> [remote]:
get) work with either session mode; uploads (put) require read-write access, since writes fail on a read-only mount. get requests a read-only session but can reuse your read-write session; put opens or reuses a read-write session. The default local destination for get is .; the default remote destination for put is /. Remote paths are relative to the volume root: /datasets/my-data in put is /volume/datasets/my-data inside SSH.
Stop a session using the ID printed when it opens:
Use a volume for training
Pass a volume name when launching a full fine-tuning run:[deployment] block. Volumes are not supported for LoRA runs.
If the volume is missing from the selected team or personal account, the CLI creates it (default 1Ti), waits until it is RUNNING, then dispatches the run. Set --volume-size to choose its initial size; existing volumes are left unchanged. The run writes its outputs under runs/<runId>/ on the volume, giving each run its own directory.
A config with a [data] block and no [trainer] or [orchestrator] block auto-dispatches as Hosted SFT, mounting the volume read-only at /volume for data.name to read the staged dataset.
The volume pins the run to the cluster where it was created. That cluster must support the run’s GPU requirements and have the base model cached; the run cannot move to another cluster just because it has free GPUs.
You can also set the volume at the top level of your TOML config, before any tables:
--volume and --volume-size flags take precedence over their config values.
Grow a volume
Pass a new size larger than the current size, up to10Ti:
Delete a volume
--yes (or -y) to skip the prompt.
Team volumes require a team admin to delete them; personal volumes can be deleted by their owner.
Deletion is refused while the volume is still provisioning or runs are still mounting it. Wait for those runs to finish, or stop them and wait for their pods to terminate, then retry. --yes skips only the confirmation; it does not bypass this guard.