AI & Machine Learning
Nanogpt Training
Train GPT-2 scale models (~124M parameters) efficiently on a single GPU. Covers GPT-124M architecture, tokenized dataset loading (e.g., HuggingFace Hub shards), modern optimizers (Muon, AdamW), mixed precision training, and training loop implementation.
- Publisher / source
- benchflow-ai/skillsbench (found on GitHub top repositories)
- Upstream record
- benchflow-ai/skillsbench
- Version
- Version 1
- Published
- Publication review
- Approved for publication
- Content fingerprint
c51a9d618912545c6cbe9c0bdbcc5630a723280edbea29e4653558c3aa394efe