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The training material comprised 28,035 volumes, processed into approximately 2.93 billion filtered tokens. With about 340 million parameters, its architecture mirrors GPT-2-Medium's scale. The distinguishing characteristic lies in its exclusive training on historical documents, unlike GPT-2's modern training corpus.

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