| # Local checkpoints (not in Git) | |
| Trained weights live here so clones stay small. After cloning, install the published bundle: | |
| ```bash | |
| cd polyguard-rl | |
| python scripts/install_hf_active_bundle.py | |
| ``` | |
| That creates **`active/`** with: | |
| | Path | Contents | | |
| |------|----------| | |
| | `active/active_model_manifest.json` | Which artifact to load (GRPO vs merged vs SFT) | | |
| | `active/grpo_adapter/` | PEFT GRPO adapter (+ tokenizer files) | | |
| | `active/merged/` | Full merged Qwen 0.5B weights (~1 GB) | | |
| | `active/sft_adapter/` | SFT LoRA fallback | | |
| A Hub cache copy may also appear under `.hf_bundles/` (safe to delete after a successful install). | |
| Enable in `.env`: `POLYGUARD_ENABLE_ACTIVE_MODEL=true` and `POLYGUARD_HF_MODEL=Qwen/Qwen2.5-0.5B-Instruct` (base for the adapter path). | |
| **If this folder looks empty in the editor:** run the install command above; then confirm with `ls active/`. | |