---
license: mit
tags:
  - chess
  - reinforcement-learning
  - pytorch
---

# exp182 / exp183 — 309M ChessTransformer (A40 run)

## Models

### Pretrain (`latest.pt` / `pretrain_step10000.pt`)
- **309M** deep-narrow ChessTransformer (96L × 512d, 8 heads)
- StrengthenedBoardEncoder + SwiGLU + chess relative bias
- Muon pretrain to **step 10,000** / 50k target (batch=192, bf16)
- Repo file: uploaded as `pretrain_step10000.pt` and `latest_pretrain.pt`

### RL (`rl_iter010.pt`)
- Expert-iteration RL from the step-10k pretrain
- Soft MCTS visit targets + hard Stockfish moves (full strength, depth 8)
- Checkpoint after **iteration 10**

## Usage
```python
from huggingface_hub import hf_hub_download
from chess_inference import load_checkpoint

path = hf_hub_download("avewright/exp182-pretrain-309m", "rl_iter010.pt")
model = load_checkpoint(path, device="cuda")
```

Code: https://github.com/avewright/transform