---
license: cc-by-nc-4.0
tags:
  - arkadiko
  - checkpoint
  - resume-only
---

# Arkadiko V4 — Raw Training Checkpoints

**For resume-training and reproducibility only. Not the artifact you want to load for inference or SFT.**

For a clean inference/SFT artifact see [VectorNomad/arkadiko-v4-base](https://huggingface.co/VectorNomad/arkadiko-v4-base).

## Files

| File | Size | Step | What |
|---|---|---|---|
| `final.pt` | ~1.28 GB | 9,114,584 | End-of-run checkpoint. Last optimizer step before training terminated. |
| `latest.pt` | ~1.28 GB | ~9,113,000 | Atomic-save predecessor. Kept as a safety copy. |

Each `.pt` is a Python pickle (`torch.save`) with these top-level keys:

- `step` — global step
- `total_tokens` — tokens consumed
- `subphase_idx` — curriculum subphase (15 = final)
- `config` — `ArkadikoConfig` dataclass instance (requires the project repo to unpickle)
- `model` — state_dict (131 entries, 213.9M bf16 params)
- `optimizer` — AdamW state (exp_avg, exp_avg_sq for every param + LR/beta groups)

## Loading

Requires the `arkadiko` package on `sys.path` (the project repo is private). Without it, `torch.load` raises `ModuleNotFoundError: No module named 'arkadiko'` because the pickled `ArkadikoConfig` references it.

```python
import sys; sys.path.insert(0, "/path/to/arkadiko-repo")
import torch
ckpt = torch.load("final.pt", map_location="cpu", weights_only=False)
print(ckpt["step"], ckpt["total_tokens"])
```

For inference-only use of the weights, prefer the `safetensors` artifact in the [base repo](https://huggingface.co/VectorNomad/arkadiko-v4-base).

## License

CC BY-NC 4.0.