Downloads · 30 days
6
15% of all-time downloads
chess-transformer-200m-compact-soft
avewright/chess-transformer-200m-compact-soft
chess-transformer-200m-compact-soft is a machine learning model from avewright. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as mit.
Finetune of avewright/chess-transformer-200m-latest onto compact move vocab (1968) using local Stockfish MultiPV soft targets (avewright/exp186-sf-multipv-2m).
All-time downloads
41
Public
Repo size
2.4 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.pt2.4 GB · 100%
At a glance
- Library
- pytorch
- License
- mit
- Access
- Public
- Created
- Jul 10, 2026
- Updated
- Jul 10, 2026
- SHA
- 0ea45525
Model card
From the Hugging Face model README
Chess Transformer 200M (compact vocab + soft MultiPV FT)
Finetune of avewright/chess-transformer-200m-latest
onto compact move vocab (1968) using local Stockfish MultiPV soft targets
(avewright/exp186-sf-multipv-2m).
Checkpoint
- File:
best_model.pt(exp188best.ptsnapshot) - 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
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
- Library
- pytorch
- License
- mit
- Created
- Jul 10, 2026
- Updated
- Jul 10, 2026