# AutoModel Launcher And Executor Context

Use this pack only when a user asks how to run an AutoModel SFT/PEFT step on a
specific execution backend. It is not the source of the training schema; read
`../CATALOG.md` and `../COMMANDS.md` first, then verify the selected step config
and `src/nemotron/steps/_runners/automodel.py` for live run details.

## Contract

- Prefer the repo-native command:
  `uv run nemotron steps run sft/automodel -c <config>`.
- For remote execution, use the active env TOML and choose a real profile. Do
  not infer `--batch` from examples or naming conventions.
- Do not generate custom launcher Python when a step config plus env profile can
  express the run.
- Keep secrets in environment variables referenced by env TOML or the runtime
  environment, not in generated YAML.

## Backend Selection

| Situation | Use |
|---|---|
| Local wiring smoke test | `-c tiny --dry-run` first, then local run only if hardware is available |
| Lepton or DGX Cloud submission | `--batch <profile>` from `NEMOTRON_ENV_FILE` or repo-root `env*.toml` |
| Slurm submission | Slurm env TOML profile with the container, mounts, and env vars already defined |
| Missing env file | Stop and ask for/generate env TOML; do not invent a batch profile |

## Live Verification

After the bundled references select AutoModel, verify:

1. `src/nemotron/steps/sft/automodel/step.toml` or
   `src/nemotron/steps/peft/automodel/step.toml`.
2. The selected `config/tiny.yaml` or `config/default.yaml`.
3. `src/nemotron/steps/_runners/automodel.py` for the exact command shape.
4. Active env TOML sections when remote execution is requested.

## Config Rules

- AutoModel consumes chat-format JSONL, not packed Parquet.
- Keep `model.pretrained_model_name_or_path`, dataset path, tokenizer/chat
  template assumptions, and output directory explicit.
- Use `peft=lora` or a LoRA block for adapter tuning; use full SFT only when the
  user has enough GPU memory and wants a full checkpoint.
- For adapter output, plan `convert/merge_lora` if the final artifact must be a
  standalone HF checkpoint.

## Failure Modes

- If `uv run nemotron steps run ... --dry-run` cannot locate the config, use the
  full config path instead of an alias.
- If a remote submission lacks mounts for data/checkpoint paths, fix the env
  profile before running the job.
- If W&B is enabled in the training config or env, require `WANDB_API_KEY` in
  the environment.