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Upload ChessBot Chess model

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  1. .gitignore +125 -0
  2. README.md +1 -17
.gitignore ADDED
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+ # Python cache files
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+ __pycache__/
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+ *.py[cod]
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+ *$py.class
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+
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+ # Distribution / packaging
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+ .Python
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+ build/
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+ develop-eggs/
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+ dist/
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+ downloads/
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+ eggs/
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+ .eggs/
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+ lib/
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+ lib64/
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+ parts/
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+ sdist/
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+ var/
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+ wheels/
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+ *.egg-info/
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+ .installed.cfg
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+ *.egg
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+ MANIFEST
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+
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+ # PyInstaller
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+ *.manifest
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+ *.spec
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+
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+ # Installer logs
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+ pip-log.txt
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+ pip-delete-this-directory.txt
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+
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+ # Unit test / coverage reports
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+ htmlcov/
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+ .tox/
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+ .nox/
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+ .coverage
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+ .coverage.*
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+ .cache
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+ nosetests.xml
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+ coverage.xml
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+ *.cover
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+ .hypothesis/
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+ .pytest_cache/
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+
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+ # Translations
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+ *.mo
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+ *.pot
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+
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+ # Django stuff:
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+ *.log
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+ local_settings.py
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+ db.sqlite3
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+
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+ # Flask stuff:
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+ instance/
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+ .webassets-cache
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+
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+ # Scrapy stuff:
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+ .scrapy
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+
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+ # Sphinx documentation
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+ docs/_build/
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+
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+ # PyBuilder
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+ target/
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+
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+ # Jupyter Notebook
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+ .ipynb_checkpoints
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+
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+ # IPython
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+ profile_default/
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+ ipython_config.py
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+
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+ # pyenv
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+ .python-version
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+
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+ # celery beat schedule file
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+ celerybeat-schedule
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+
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+ # SageMath parsed files
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+ *.sage.py
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+
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+ # Environments
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+ .env
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+ .venv
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+ env/
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+ venv/
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+ ENV/
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+ env.bak/
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+ venv.bak/
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+
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+ # Spyder project settings
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+ .spyderproject
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+ .spyproject
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+
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+ # Rope project settings
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+ .ropeproject
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+
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+ # mkdocs documentation
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+ /site
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+
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+ # mypy
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+ .mypy_cache/
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+ .dmypy.json
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+ dmypy.json
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+
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+ # Pyre type checker
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+ .pyre/
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+
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+ # IDE
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+ .vscode/
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+ .idea/
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+ *.swp
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+ *.swo
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+ *~
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+
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+ # OS
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+ .DS_Store
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+ .DS_Store?
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+ ._*
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+ .Spotlight-V100
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+ .Trashes
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+ ehthumbs.db
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+ Thumbs.db
README.md CHANGED
@@ -44,23 +44,7 @@ model = model.to(device)
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  # Get the best move
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  move = model.get_move_from_fen_no_thinking(fen, T=0.1, device=device)
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- print(f"Policy-based move: {move}")
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-
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- # Get the best move using value
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- value_move = model.get_best_move_value(fen, T=0, device=device)
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- print(f"Value-based move: {value_move}")
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-
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- # Get position evaluation
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- position_value = model.get_position_value(fen, device=device)
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- print(f"Position value [black_win, draw, white_win]: {position_value}")
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-
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- # Get move probabilities
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- probs = model.get_move_from_fen_no_thinking(fen, T=1, device=device, return_probs=True)
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- top_moves = sorted(probs.items(), key=lambda x: x[1], reverse=True)[:5]
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- print("Top 5 moves:")
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- for move, prob in top_moves:
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- print(f" {move}: {prob:.4f}")
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-
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  ```
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  ## Requirements
 
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  # Get the best move
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  move = model.get_move_from_fen_no_thinking(fen, T=0.1, device=device)
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+ print(f"Predicted move: {move}")
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ```
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  ## Requirements