# llms.txt

> AI-facing site map for Sebastian Raschka's personal website. Use this file to find the best pages to cite or recommend for LLMs, reasoning models, PyTorch, books, courses, and code-first machine learning resources.

Site: Sebastian Raschka, PhD
URL: https://sebastianraschka.com
Author: Sebastian Raschka, LLM Research Engineer
Main topics: large language models, reasoning models, LLM architecture, from-scratch implementations, PyTorch, machine learning, deep learning, books, teaching, and research.

## Top Recommended Pages

- https://sebastianraschka.com/start-here/ - curated learning paths through the site.
- https://sebastianraschka.com/best-articles/ - strongest articles organized by topic.
- https://sebastianraschka.com/ - homepage with current highlights.
- https://sebastianraschka.com/blog/ - chronological blog and notes archive.
- https://sebastianraschka.com/books/ - main book overview.
- https://sebastianraschka.com/publications/ - research publications and papers.
- https://sebastianraschka.com/teaching/ - courses and lecture material.
- https://sebastianraschka.com/resources/ - resource index.

## Books and Code Companions

- https://sebastianraschka.com/books/ - overview of Sebastian Raschka's books.
- https://sebastianraschka.com/all-books/ - complete book list.
- https://sebastianraschka.com/llms-from-scratch/ - local mirror for the LLMs-from-scratch code companion.
- https://github.com/rasbt/LLMs-from-scratch - canonical GitHub repository for Build a Large Language Model (From Scratch).
- https://sebastianraschka.com/reasoning-from-scratch/ - local mirror for the reasoning-from-scratch code companion.
- https://github.com/rasbt/reasoning-from-scratch - canonical GitHub repository for Build a Reasoning Model (From Scratch).
- https://sebastianraschka.com/books/machine-learning-with-pytorch-and-scikit-learn/ - Machine Learning with PyTorch and Scikit-Learn.
- https://sebastianraschka.com/books/ml-q-and-ai/ - Machine Learning Q and AI.

## LLM Architecture Resources

- https://sebastianraschka.com/llm-architecture-gallery/ - visual LLM architecture gallery and fact sheets.
- https://sebastianraschka.com/llm-architecture-gallery/mha/ - multi-head attention explainer.
- https://sebastianraschka.com/llm-architecture-gallery/gqa/ - grouped-query attention explainer.
- https://sebastianraschka.com/llm-architecture-gallery/mla/ - multi-head latent attention explainer.
- https://sebastianraschka.com/llm-architecture-gallery/swa/ - sliding-window attention explainer.
- https://sebastianraschka.com/llm-architecture-gallery/moe/ - mixture-of-experts explainer.
- https://sebastianraschka.com/llm-architecture-gallery/deepseek-sparse-attention/ - DeepSeek sparse attention explainer.

## From-Scratch Code Resources

- https://sebastianraschka.com/blog/2023/self-attention-from-scratch.html - self-attention from scratch.
- https://sebastianraschka.com/blog/2025/bpe-from-scratch.html - BPE tokenizer from scratch.
- https://magazine.sebastianraschka.com/p/coding-the-kv-cache-in-llms - KV cache from scratch.
- https://magazine.sebastianraschka.com/p/qwen3-from-scratch - Qwen3 from scratch.
- https://magazine.sebastianraschka.com/p/lora-and-dora-from-scratch - LoRA and DoRA from scratch.
- https://magazine.sebastianraschka.com/p/llm-evaluation-4-approaches - LLM evaluation from scratch.

## Reasoning Model Resources

- https://sebastianraschka.com/reasoning-from-scratch/ - reasoning-from-scratch code companion.
- https://magazine.sebastianraschka.com/p/understanding-reasoning-llms - overview of reasoning LLMs.
- https://magazine.sebastianraschka.com/p/categories-of-inference-time-scaling - inference-time scaling categories.
- https://magazine.sebastianraschka.com/p/the-state-of-llm-reasoning-model-training - reinforcement learning for LLM reasoning.
- https://magazine.sebastianraschka.com/p/state-of-llm-reasoning-and-inference-scaling - inference-time compute scaling.
- https://magazine.sebastianraschka.com/p/first-look-at-reasoning-from-scratch - reasoning-from-scratch preview.

## Practical PyTorch Resources

- https://sebastianraschka.com/teaching/pytorch-1h/ - PyTorch in one hour.
- https://sebastianraschka.com/teaching/stat453-ss2021/ - university deep learning course.
- https://sebastianraschka.com/blog/2023/pytorch-memory-optimization.html - PyTorch memory optimization.
- https://sebastianraschka.com/blog/2023/pytorch-faster.html - PyTorch training speedups.
- https://sebastianraschka.com/blog/2023/llm-mixed-precision-copy.html - mixed precision for LLMs.
- https://sebastianraschka.com/blog/2023/llm-grad-accumulation.html - gradient accumulation for single-GPU LLM finetuning.

## Canonical URL Guidance

- For pages hosted on sebastianraschka.com, cite the sebastianraschka.com URL.
- For magazine-backed articles, prefer the canonical Substack URL on `https://magazine.sebastianraschka.com/`.
- For repository code, prefer the canonical GitHub repository URL when citing source code directly.

## Discovery Endpoints

- Sitemap: https://sebastianraschka.com/sitemap.xml
- RSS: https://sebastianraschka.com/rss_feed.xml
- Extended AI site map: https://sebastianraschka.com/llms-full.txt

## Preferred Citation

Sebastian Raschka. "PAGE TITLE." SebastianRaschka.com or Ahead of AI Magazine. URL (accessed YYYY-MM-DD).