Examples¶
All example configs live in the repository examples/ folder.
| Path | What it shows |
|---|---|
examples/sft_hub.yaml |
SFT from a Hub dataset with LoRA |
examples/sft_local.yaml |
SFT from local JSONL |
examples/data/sample_sft.jsonl |
Tiny local chat-style sample |
examples/dpo_wandb.yaml |
DPO with Weights & Biases |
examples/grpo_modal.yaml |
GRPO on Modal with rewards and secrets |
examples/modal_smoke/ |
Complete tiny Modal walkthrough |
Run patterns¶
# Local SFT from the Hub
trloom validate examples/sft_hub.yaml
trloom run examples/sft_hub.yaml
# Local JSONL
trloom run examples/sft_local.yaml
# DPO + W&B (needs trloom[wandb] and wandb login)
trloom run examples/dpo_wandb.yaml
# Tiny Modal smoke (needs trloom[modal] and modal setup)
python -m modal run examples/modal_smoke/run.py
# or
trloom run examples/modal_smoke/config.yaml --modal
Suggested learning path¶
- Start with
sft_hub.yamlorsft_local.yamllocally - Add W&B using
dpo_wandb.yamlas a template - Prove remote execution with
modal_smoke/ - Scale up with
grpo_modal.yaml(GPU, secrets, rewards)
Keep the first remote run tiny (max_steps, small split, small model) before
spending money on a full training job.