SUMMARY AI要約 by gpt-5-mini
A concise, from-scratch GPT implementation assembled while completing the NeetCode ML course (authored by Stefano, May 8, 2026). It’s an educational codebase intended for students, learners, and engineers who want to study or reproduce transformer/GPT internals by reading and running plain Python implementations. Key features: - Full transformer/GPT stack: attention head, multi-head attention, transformer block, GPT model. - Inference optimizations: KV-cache and grouped query attention. - Multiple normalization implementations (Layer, Batch, RMS). - Tokenization and data pipeline: BPE tokenizer, character vocab, dataset loader, preprocessing utilities. - Lower-level foundations built from scratch: neurons, backprop, MLP, activations, loss, training loop. - Scripts to train and generate text (train.py, generate.py). Quick start via requirements and those scripts.
使用言語(バイト数比)
オーナー情報
SWE @Uber | ex-Amazon
日付
| GitHub作成日 | 2026-05-08 |
| 最終Push | 2026-05-09 |
| 当サイト初検出 | 2026-05-09 |
| 最終取得 | 2026-05-09 18:15 |
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