--- title: "#transformers articles | Hashnode" description: "Explore 538 articles tagged #transformers on Hashnode. Tutorials, guides, and how-tos from the community." url: "https://hashnode.com/tag/transformers" --- Tag # #transformers 538 posts · 46 followers [Pratyush Ranjan](https://hashnode.com/@pratyushranjan02) · [5d ago](https://hashnode.com/posts/paged-attention-in-ai-inference/6aeed0a74f4b146adf854c72) ### [Paged Attention in AI Inference](https://ai-inference-pratyush.hashnode.dev/paged-attention-in-ai-inference?utm_source=hashnode&utm_medium=feed) Learn how paged attention cuts KV cache waste. Build a mini version in PyTorch and benchmark memory use against a contiguous cache. 9 min read · [ai-inference-pratyush.hashnode.dev](https://ai-inference-pratyush.hashnode.dev/paged-attention-in-ai-inference?utm_source=hashnode&utm_medium=feed) [1](https://hashnode.com/posts/paged-attention-in-ai-inference/6aeed0a74f4b146adf854c72) [AheadMint](https://hashnode.com/@aheadmint) · [Oct 31](https://hashnode.com/posts/following-one-sentence-through-a-transformer-a-tensor-shape-walkthrough/6ae5c08dde78f2f2e8eca23e) ### [Following One Sentence Through a Transformer: A Tensor-Shape Walkthrough](https://aheadmint.hashnode.dev/following-one-sentence-through-a-transformer-a-tensor-shape-walkthrough?utm_source=hashnode&utm_medium=feed) What actually happens to "Transformers understand context" inside the model, step by step 3 min read · [aheadmint.hashnode.dev](https://aheadmint.hashnode.dev/following-one-sentence-through-a-transformer-a-tensor-shape-walkthrough?utm_source=hashnode&utm_medium=feed) [ZyVOP](https://hashnode.com/@zyvop) · [Oct 25](https://hashnode.com/posts/i-built-the-smallest-llm-i-could-to-understand-how-they-work-c49fr/6adde001a8cddc47e4d2bb5a) ### [I Built the Smallest LLM I Could to Understand How They Work](https://blog.zyvop.com/i-built-the-smallest-llm-i-could-to-understand-how-they-work-c49fr?utm_source=hashnode&utm_medium=feed) A hands-on walkthrough of a ~108k-parameter character-level GPT in under 200 lines of PyTorch, with the full code included. 12 min read · [blog.zyvop.com](https://blog.zyvop.com/i-built-the-smallest-llm-i-could-to-understand-how-they-work-c49fr?utm_source=hashnode&utm_medium=feed) [Nishanthan Karunakaran](https://hashnode.com/@nishanthan) · [Oct 22](https://hashnode.com/posts/how-query-key-and-value-qkv-work-in-transformers/6ad9c78da2619bfccea4aca7) ### [How Query, Key, and Value (QKV) Work in Transformers](https://nishanthan.hashnode.dev/how-query-key-and-value-qkv-work-in-transformers?utm_source=hashnode&utm_medium=feed) Every Transformer-based language model, from BERT to GPT, relies on a mechanism called attention to determine how different tokens in a sequence relate to one another. At the heart of this mechanism a 7 min read · [nishanthan.hashnode.dev](https://nishanthan.hashnode.dev/how-query-key-and-value-qkv-work-in-transformers?utm_source=hashnode&utm_medium=feed) [Sai Sandeep Kantareddy](https://hashnode.com/@skantar1) · [Oct 20](https://hashnode.com/posts/routing-ai-requests-without-training-data-and-knowing-when-to-train-a-classifier/6ad6ef8f2200e367f74f72af) ### [Routing AI Requests Without Training Data and Knowing When to Train a Classifier](https://tokenbytoken.hashnode.dev/routing-ai-requests-without-training-data-and-knowing-when-to-train-a-classifier?utm_source=hashnode&utm_medium=feed) The retail examples below are illustrative; they do not report measured production results or disclose an employer's implementation. A team adds three specialist agents to an assistant. Routing looks 9 min read · [tokenbytoken.hashnode.dev](https://tokenbytoken.hashnode.dev/routing-ai-requests-without-training-data-and-knowing-when-to-train-a-classifier?utm_source=hashnode&utm_medium=feed) [3](https://hashnode.com/posts/routing-ai-requests-without-training-data-and-knowing-when-to-train-a-classifier/6ad6ef8f2200e367f74f72af) [Nishanthan Karunakaran](https://hashnode.com/@nishanthan) · [Oct 15](https://hashnode.com/posts/understanding-transformer-the-architecture-behind-modern-ai/6ad04aba652296781d0156e8) ### [Understanding Transformer: The Architecture Behind Modern AI](https://nishanthan.hashnode.dev/understanding-transformer-the-architecture-behind-modern-ai?utm_source=hashnode&utm_medium=feed) What Is a Transformer? A Transformer is a neural network architecture introduced by Google researchers in 2017 in the paper Attention Is All You Need. It uses attention mechanisms to help the model le 6 min read · [nishanthan.hashnode.dev](https://nishanthan.hashnode.dev/understanding-transformer-the-architecture-behind-modern-ai?utm_source=hashnode&utm_medium=feed) [Mahesh Moholkar](https://hashnode.com/@maheshmoholkar) · [Oct 13](https://hashnode.com/posts/building-a-modern-llm-from-scratch-rmsnorm-rope-gqa-and-swiglu/6ace38076361ea8b3dee6838) ### [Building a Modern LLM from Scratch: RMSNorm, RoPE, GQA and SwiGLU](https://maheshmoholkar.hashnode.dev/building-a-modern-llm-from-scratch-rmsnorm-rope-gqa-and-swiglu?utm_source=hashnode&utm_medium=feed) What changed inside the transformer since 2017, why every open model made the same four changes, and a 250-line model you can train on Shakespeare tonight. 43 min read · [maheshmoholkar.hashnode.dev](https://maheshmoholkar.hashnode.dev/building-a-modern-llm-from-scratch-rmsnorm-rope-gqa-and-swiglu?utm_source=hashnode&utm_medium=feed) [ZyVOP](https://hashnode.com/@zyvop) · [Oct 3](https://hashnode.com/posts/build-a-small-llm-from-scratch-a-tested-gpt-in-pytorch/6ac08645a27ad90ccd5d489f) ### [Build a Small LLM From Scratch: A Tested GPT in PyTorch](https://blog.zyvop.com/build-a-small-llm-from-scratch-a-tested-gpt-in-pytorch?utm_source=hashnode&utm_medium=feed) Build a compact GPT-style transformer in PyTorch, train it on Tiny Shakespeare, test the critical pieces, and see exactly how an 813K-parameter language model learns. 26 min read · [blog.zyvop.com](https://blog.zyvop.com/build-a-small-llm-from-scratch-a-tested-gpt-in-pytorch?utm_source=hashnode&utm_medium=feed) [Surendranath Reddy Jillella](https://hashnode.com/@jsnreddy) · [Sep 24](https://hashnode.com/posts/we-tested-typesafe-ai-s-jev-on-screen-classification-20x-faster-153x-cheaper-and-noticeably-less-accurate/6ab50209fa7bc60019226461) ### [We Tested TypeSafe AI's Jev on Screen Classification: 20x Faster, 153x Cheaper, and Noticeably Less Accurate](https://qapilot-ai.hashnode.dev/we-tested-typesafe-ai-s-jev-on-screen-classification-20x-faster-153x-cheaper-and-noticeably-less-accurate?utm_source=hashnode&utm_medium=feed) Jev promises faster, cheaper alternative to LLMs for structured decisions, so we tested on a task at QApilot: classify screens for mobile app agents. 9 min read · [qapilot-ai.hashnode.dev](https://qapilot-ai.hashnode.dev/we-tested-typesafe-ai-s-jev-on-screen-classification-20x-faster-153x-cheaper-and-noticeably-less-accurate?utm_source=hashnode&utm_medium=feed) [2](https://hashnode.com/posts/we-tested-typesafe-ai-s-jev-on-screen-classification-20x-faster-153x-cheaper-and-noticeably-less-accurate/6ab50209fa7bc60019226461) [Ekansh Nangia](https://hashnode.com/@ekanshn) · [Sep 17](https://hashnode.com/posts/introduction-to-mechanistic-interpretability/6aaba1e727577e90301e1109) ### [Introduction To Mechanistic Interpretability](https://ekanshn.hashnode.dev/introduction-to-mechanistic-interpretability?utm_source=hashnode&utm_medium=feed) How do LLMs actually work? Explore mechanistic interpretability, AI epistemology, and why probing neural networks cannot crack the AI black box. 18 min read · [ekanshn.hashnode.dev](https://ekanshn.hashnode.dev/introduction-to-mechanistic-interpretability?utm_source=hashnode&utm_medium=feed)