Blocks
sft
Supervised fine-tuning on trajgen's SFT data
sft is the supervised fine-tuning stage. It reads LLaMA-Factory LF-format SFT data produced by trajgen, then trains a base model with LLaMA-Factory + DeepSpeed ZeRO-3 across 8 GPUs.
Full docs: coming soon — paste the sft docs URL here when published (e.g. https://swe-sft-docs.pages.dev/docs).
Docs site not published yet
The sft block does not yet have a standalone documentation site. Once it ships, replace the placeholder above with the live URL. For now, the agent contract in subblock/sft/CLAUDE.md is the source of truth.
At a glance
- Inputs:
source,conversion,model,training,infrastructure,credentials. The training data dependency is typically wired fromtrajgen.output.sft_data_dir. - Output:
checkpoint_path—subblock/sft/artifacts/model/<run>/(consumed byrlas the starting actor). - Runs: Local (8× GPU). Long-running.
How to run
/sft:setup # install LLaMA-Factory, register dataset, fill defaults
/sft:check # preflight: GPUs, DeepSpeed config, dataset, base model
/sft:run # launch training
/sft:dashboard # parse the latest training log + WandB URLReference
- Block contract:
subblock/sft/CLAUDE.md - Full docs site: coming soon