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Move enc to gloabal namespace
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@ -16,6 +16,8 @@ num_proc = 8
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# it is better than 1 usually though
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num_proc_load_dataset = num_proc
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enc = tiktoken.get_encoding("gpt2")
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if __name__ == '__main__':
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# takes 54GB in huggingface .cache dir, about 8M documents (8,013,769)
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dataset = load_dataset("openwebtext", num_proc=num_proc_load_dataset)
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@ -38,7 +40,6 @@ if __name__ == '__main__':
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# })
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# we now want to tokenize the dataset. first define the encoding function (gpt2 bpe)
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enc = tiktoken.get_encoding("gpt2")
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def process(example):
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ids = enc.encode_ordinary(example['text']) # encode_ordinary ignores any special tokens
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ids.append(enc.eot_token) # add the end of text token, e.g. 50256 for gpt2 bpe
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