Navigate and review
Select settings, validate the configuration, and inspect the dataset before reviewing a
launch. Preview and review capture data in the background. Esc abandons an outdated read
without letting a late result reopen a launch screen. A separate Enter in the displayed
review starts work.
Runs retain IDs, plan checksums, metrics, logs, provider handles, and known failures. Reopen
the same workspace to reconnect. Select an agent-prepared run and press
r to review and
launch that same ID. c reuses settings for a new run; it does not restore optimizer state.
Training data
Studio SFT uses text-only chat JSONL: an optional initial system message, alternating user/assistant turns, and a final assistant target. Message content must be nonempty text.Backends and billing
RunPod’s ceiling excludes ancillary costs. Modal and River have no enforced dollar ceiling
in this integration. River manages hardware and rejects GPU overrides. Local readiness
does not authenticate any provider or certify that a model fits a GPU.
Remote jobs retain the reviewed framework release identity. Modal installs the matching
published release remotely rather than uploading uncommitted local source. A reviewed RunPod
development wheel can be snapshot-bound by hash. Neither mechanism attests the entire remote
dependency/runtime environment. Confirm publication and backend support before live use.
RunPod/Modal details expose retained submission IDs, allocation intent, and cleanup
acknowledgements. Inspect them with
finetune provider-status RUN_ID. These are local
observations, not live provider status. An interrupted allocation may have succeeded without
returning an ID; a cleanup acknowledgement does not establish that charges stopped.
Checkpoints, stopping, and quality
Set a training seed independently of evaluation randomness. A full model commit is required for exact recovery; an unpinned run does not acquire reproducible identity from its model name. Local native RL can setcheckpoint_every to a positive committed-update interval, capped
at 100 planned checkpoints. Zero keeps final-only behavior. SFT saves epoch checkpoints;
remote backends do not support this native interval setting.
k opens a checksum-bound cooperative local stop. Prepared runs cancel immediately; queued
workers check before loading; active SFT stops at a step boundary and native RL saves after
a committed update. A stop request does not kill a PID or confirm immediate exit. Remote
cleanup remains provider-specific.
z inspects exact recovery; j manages local paired evaluation and checkpoint validation.
These workflows require their own reviews. Read recovery and evaluation
before treating a checkpoint or successful run as a quality result.
Small terminals
Phone-sized panes work from 32 columns × 16 rows. Below 72 × 22, compact navigation uses2/8 to move, 3/9 to page, 0 to go back, and 4 to switch main screens outside editors.
Digits remain literal in editors and search. An undersized resize pauses actions, including
hidden confirmation keys.
docs/FINETUNING_TUI.md and the live finetune schema from the reviewed checkout.
Start with the preparation quickstart.