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How LLMs Actually Work
Hacker News (AI keywords)10 days agoTutorialThe article explains how modern LLMs convert text into token IDs, embeddings, and position-aware vectors before passing them through stacked transformer blocks. It covers attention, multi-head attention, KV cache, GQA, feed-forward networks, MoE, residual streams, normalization, and decoding. Its goal is educational: helping readers understand the common architecture behind many current model families and read model cards or papers more confidently.
Transformers v5 中的 Tokenization：更簡單、更清晰、且更具模組化★ 82
Hugging Face Blog178 days agoReleaseIn the development process of natural language processing (NLP) and large language models (LLMs), tokenization is the first step in model input and also the…