H64LM: A 249M-parameter Mixture-of-Experts Transformer built from scratch in PyTorch [P]
Hi everyone, I built H64LM, a research project to better understand modern LLMs by implementing one from scratch in PyTorch. Instead of relying on high-level training frameworks, I implemented the core components myself attention, MoE routing, normalization, and the training loop
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Technical breakdown
Hi everyone, I built H64LM, a research project to better understand modern LLMs by implementing one from scratch in PyTorch. Instead of relying on high-level training frameworks, I implemented the core components myself attention, MoE routing, normalization, and the training loop. Features 249M-parameter Transformer Grouped Query Attention (GQA) Sparse Mixture-of-Experts (8 experts, Top-2 routi
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