README.md

metadata

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.

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.

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.

License

CC BY-NC 4.0.