About This Project
A language model trained from scratch exclusively on data from certain places and time periods to reduce modern bias and emulate the voice, vocabulary, and worldview of the era. Focuses on curating historical data and building a custom tokenizer.
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Installation & Setup
1. Gather and Prepare Historical Texts (.txt files). 2. Build a Custom Tokenizer (run train_tokenizer.py). 3. Train Your Model (refer to nanoGPT).
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