Portable PyTorch evaluation and chess-decision evidence for lc0-family models.
Install the package. Use the hub extra for the example below:
pip install "lczerolens[hub]"Evaluate a position:
import chess
from lczerolens import LczeroEvaluator, LczeroModel
model = LczeroModel.from_hf("lczerolens/maia-1100")
evaluator = LczeroEvaluator(model)
evaluation = evaluator.evaluate(chess.Board())
print(evaluation.policy.best_move)
print(evaluation.policy["e2e4"].probability)- Model inputs and loading
- Evaluate positions and batches
- Chess evidence: moves, lines, puzzles, and counterfactuals
- Search and replay
- Complete decision-analysis tutorial
For the package boundary and detailed guides, see the documentation.
See CONTRIBUTING.md. Development and test commands live there rather than in the quick-start path.
If you use lczerolens in research, cite the version you used. The canonical
metadata is in CITATION.cff.
@software{poupart_lczerolens_2026,
author = {Poupart, Yoann},
title = {LczeroLens},
version = {0.5.0},
year = {2026},
url = {https://github.com/Xmaster6y/lczerolens}
}lczerolens is licensed under the MIT License. See LICENSE for details.