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import sentencepiece as spm |
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spm.SentencePieceTrainer.train(input="/researchdisk/training_dataset_sentences/train.txt", model_prefix="tokenizer", |
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model_type="bpe", split_digits=True, vocab_size=64256, byte_fallback=True, |
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normalization_rule_name="nfkc", |
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user_defined_symbols=["[INST]", "[/INST]", "<<SYS>>", "<</SYS>>"], |
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required_chars="abcdefghijklmnopqrstuvwxyzåäöABCDEFGHIJKLMNOPQRSTUVWXYZÅÄÖ", |
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train_extremely_large_corpus=True, |
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input_sentence_size=500000000, shuffle_input_sentence=True, |
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num_threads=96) |