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ml-training-recipes

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Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. Covers training loops, optimizer selection (AdamW, Muon), LR scheduling, mixed precision, debugging, and systematic experimentation. Use when training or fine-tuning neural networks, debugging loss spikes or OOM, choosing architectures, or optimizing GPU throughput.

When to use

• training or fine-tuning neural networks
• debugging loss spikes or OOM
• choosing architectures
• optimizing GPU throughput
• optimizer selection
• LR scheduling
• mixed precision
• systematic experimentation

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