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Upload chess-gpt-eval/main.py with huggingface_hub

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  1. chess-gpt-eval/main.py +8 -7
chess-gpt-eval/main.py CHANGED
@@ -536,24 +536,25 @@ MAX_MOVES = 999 # Due to nanogpt max input length of 1024
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  recording_file = "logs/determine.csv" # default recording file. Because we are using list [player_ones], recording_file is overwritten
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  # player_one_recording_name = "ckpt_8.pt"
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  #player_ones = ["ckpt_iter_20000.pt","ckpt_iter_40000.pt","ckpt_iter_60000.pt","ckpt_iter_80000.pt"] #["ckpt.pt"]
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- player_ones = ["50M/ckpt_9715500b.pt"]
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  player_two_recording_name = "lc0_sweep" #"stockfish_sweep"
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  move_num_in_gamestate = False
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  if __name__ == "__main__":
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  for nanogpt_player in player_ones:
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- player_one_recording_name = nanogpt_player
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  for i in range(1): #range(11):
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- num_games = 100 #265 #265 instead of 250 for duplicates (for lc0, stockfish doesn't need it)
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  # player_one = GPTPlayer(model="gpt-3.5-turbo-instruct")
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  # player_one = LocalLlamaPlayer(model_name="meta-llama/Llama-2-7b-hf")
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  # player_one = LocalLoraLlamaPlayer("meta-llama/Llama-2-7b-hf", "/workspace/axolotl/lora2-out")
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  # player_one = GPTPlayer(model="gpt-4")
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  # player_one = StockfishPlayer(skill_level=-1, play_time=0.1)
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- #player_one = NanoGptPlayer(model_name=player_one_recording_name, move_num_in_gamestate=False)
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- player_one = MambaPlayer(model_name=player_one_recording_name, move_num_in_gamestate=False)
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- #player_two = StockfishPlayer(skill_level=i, play_time=0.1)
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- player_two = LC0PLayer(skill=i)
 
 
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  # player_two = GPTPlayer(model="gpt-4")
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  # player_two = GPTPlayer(model="gpt-3.5-turbo-instruct")
 
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  recording_file = "logs/determine.csv" # default recording file. Because we are using list [player_ones], recording_file is overwritten
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  # player_one_recording_name = "ckpt_8.pt"
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  #player_ones = ["ckpt_iter_20000.pt","ckpt_iter_40000.pt","ckpt_iter_60000.pt","ckpt_iter_80000.pt"] #["ckpt.pt"]
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+ player_ones = ["50M/ckpt_12652800.pt"]
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  player_two_recording_name = "lc0_sweep" #"stockfish_sweep"
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  move_num_in_gamestate = False
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  if __name__ == "__main__":
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  for nanogpt_player in player_ones:
 
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  for i in range(1): #range(11):
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+ num_games = 500 #265 #265 instead of 250 for duplicates (for lc0, stockfish doesn't need it)
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  # player_one = GPTPlayer(model="gpt-3.5-turbo-instruct")
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  # player_one = LocalLlamaPlayer(model_name="meta-llama/Llama-2-7b-hf")
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  # player_one = LocalLoraLlamaPlayer("meta-llama/Llama-2-7b-hf", "/workspace/axolotl/lora2-out")
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  # player_one = GPTPlayer(model="gpt-4")
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  # player_one = StockfishPlayer(skill_level=-1, play_time=0.1)
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+ player_one_recording_name = nanogpt_player
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+ player_one = NanoGptPlayer(model_name=player_one_recording_name, move_num_in_gamestate=False)
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+ player_one_recording_name = "xformer_" + nanogpt_player
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+ #player_one = MambaPlayer(model_name=player_one_recording_name, move_num_in_gamestate=False)
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+ player_two = StockfishPlayer(skill_level=i, play_time=0.1)
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+ #player_two = LC0PLayer(skill=i)
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  # player_two = GPTPlayer(model="gpt-4")
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  # player_two = GPTPlayer(model="gpt-3.5-turbo-instruct")