| --- |
| license: mit |
| library_name: pytorch |
| tags: |
| - chess |
| - transformer |
| - policy |
| - soft-targets |
| - stockfish |
| --- |
| |
| # Chess Transformer 200M (compact vocab + soft MultiPV FT) |
|
|
| Finetune of [`avewright/chess-transformer-200m-latest`](https://huggingface.co/avewright/chess-transformer-200m-latest) |
| onto **compact move vocab (1968)** using local Stockfish MultiPV soft targets |
| ([`avewright/exp186-sf-multipv-2m`](https://huggingface.co/datasets/avewright/exp186-sf-multipv-2m)). |
|
|
| ## Checkpoint |
| - File: `best_model.pt` (exp188 `best.pt` snapshot) |
| - Architecture: 16L / 1024d / 16H, ~204M params, fused encoder, spatial policy, 3-class WDL |
| - Vocab: **compact 1968** (`MOVE_VOCAB_VERSION=compact`) |
| - Soft holdout top-1 at upload: **33.82%** (step 1500 of resume; training may still be running) |
|
|
| ## Load |
| ```python |
| import os |
| os.environ["MOVE_VOCAB_VERSION"] = "compact" |
| import torch |
| from huggingface_hub import hf_hub_download |
| from chess_transformer_factory import build_model, DEFAULT_200M_CONFIG |
| |
| path = hf_hub_download("avewright/chess-transformer-200m-compact-soft", "best_model.pt") |
| model = build_model(DEFAULT_200M_CONFIG) |
| ckpt = torch.load(path, map_location="cpu", weights_only=False) |
| model.load_state_dict(ckpt["model_state_dict"], strict=False) |
| model.eval() |
| ``` |
|
|
| ## Training notes |
| See `TRAINING_STATUS.md` in this repo. |
|
|
| Uploaded: 2026-07-10T02:02:52.143564+00:00 |
|
|
