Create README.md
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README.md
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---
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license: mit
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datasets:
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- nsarrazin/lichess-games-2023-01
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pipeline_tag: text-generation
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tags:
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- chess
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---
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A 231M parameter base model trained on lichess games from January 2023 that ended in checkmate (filtered out games that were won because of time).
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It's trained on sequences of UCI moves, inference is pretty simple:
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```py
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from transformers import GPT2LMHeadModel, AutoTokenizer
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model = GPT2LMHeadModel.from_pretrained("nsarrazin/chessformer").eval()
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tokenizer = AutoTokenizer.from_pretrained("nsarrazin/chessformer")
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moves = " ".join(["e2e4", "e7e5", "d2d4", "d7d5"])
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model_inputs = tokenizer(moves, return_tensors="pt")
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gen_tokens = model.generate(**model_inputs, max_new_tokens=1)[0]
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next_move = tokenizer.decode(gen_tokens[-1])
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print(next_move) #d4e5
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```
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