--- datasets: - Lichess/standard-chess-games pipeline_tag: image-feature-extraction --- - this inference endpoint has three sub endpoints defined by the dictionary in the class constructor. - all requests sent should be of the form {"inputs": data} where the data is another JSON/dictionary/js object. - the data must be of the form {"num_endpoint": int} where int is:
    0 (for testing endpoint)
    1 for creating user
    2 for the model's move - to create user embeddings, specify additional fields in data:
    "username" : chess.com username
    "pgn_content": a sinlge pgn consisting of multiple games played by the user
    "games_per_player": specify how many games in the pgn file - to get an ai_move, specify additional fields in data:
    "pgn_string" : pgn of game so far
    "color": "white" if model is playing with white pieces else "black"
    "player_centroid": player_centroid as python list generated by endpoint 1 - the pytorch model definitions are in the encoder folder, and the model weights are in the *.pt file(s).