rasbt/reasoning-from-scratch resource

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5070 stars · 777 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

The official code repository for the book 'Build a Reasoning Model (From Scratch)' by Sebastian Raschka, containing step-by-step PyTorch implementations of a reasoning LLM. It teaches how to add reasoning capabilities like chain-of-thought and RL-based fine-tuning (GRPO, RLHF) to a pre-trained base LLM for educational purposes.

Use cases

• learn how reasoning LLMs like DeepSeek R1 work internally
• implement chain-of-thought reasoning from scratch in PyTorch
• understand GRPO and RLHF fine-tuning step by step
• build a small functional reasoning model for education
• study inference-time scaling and test-time compute
• accompany a hands-on book on reasoning models

When to choose

• you want to deeply understand how reasoning models are built, not just use them
• you prefer learning by implementing in PyTorch from scratch
• you are following the Manning book and need its official code
• you want educational, well-tested notebook-based code

When to avoid

• you need a production-ready reasoning LLM or inference server
• you want pre-trained state-of-the-art models rather than educational implementations
• you need large-scale training infrastructure rather than small-scale learning code

Facets

learning-resource · maturity active

llm-training machine-learning reinforcement-learning llm-inference large-language-models deep-learning artificial-intelligence tutorials python cross-platform pytorch reasoning-models chain-of-thought rlhf grpo from-scratch book educational jupyter-notebooks

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markdown · JSON · MCP: product_card(name="rasbt/reasoning-from-scratch")