Tiny hackable CUDA language model implementation
Hacker News (AI keywords)9 days agoNew ToolThis GitHub project implements a compact generative pretrained transformer as an autoregressive byte-level sequence model. Its README describes causal self-attention, RoPE, feed-forward layers, AdamW, cross-entropy training, and BLAS/OpenBLAS-backed matrix operations, with CUDA toolkit listed in setup steps. It is most useful as an educational and experimental codebase, not as a production-grade replacement for large commercial LLMs.
從零開始在 nanoVLM 中實作 KV Cache★ 75
Hugging Face Blog375 days agoTutorialIn the inference process of large language models (LLMs) and vision-language models (VLMs), autoregressive decoding is a major performance bottleneck. Each…
你也能設計出最先進的 Transformer 位置編碼：從直覺到 RoPE 的數學推導★ 75
Hugging Face Blog566 days agoTutorialThis educational article from Hugging Face aims to guide readers — in the most intuitive, step-by-step way — to "reinvent" RoPE (Rotary Position Embedding)…
BERT 101：最先進的 NLP 模型完整原理解析
Hugging Face Blog1,565 days agoTutorialBERT (Bidirectional Encoder Representations from Transformers) is a landmark natural language processing (NLP) model proposed by Google in 2018. This Hugging…