I trained a 113M-parameter earthquake LLM from absolute scratch
A developer documents the end-to-end process of training a 113M-parameter earthquake-focused language model from scratch. The project serves as an educational resource for understanding the full lifecycle of LLM development, including data cleaning, tokenization, and multi-GPU training.
Why it matters
It provides a transparent, reproducible blueprint for small-scale AI training, demonstrating that specialized models can be developed on consumer-grade hardware.
Train a small GPT for earthquake science — the entire LLM lifecycle, from a blank folder to a talking model, explained block by block.
The content is a technical tutorial focused on engineering methodology without political or social commentary.
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