tanishqkumar/beyond-nanogpt resource

Health v2 · maintenance only

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1340 stars · 112 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

An educational repository of minimal, annotated, from-scratch implementations of ~100 modern deep learning techniques, bridging nanoGPT and research-level work. It covers LLM techniques, attention variants, generative models, reinforcement learning, and GPU systems fundamentals, all runnable on a single GPU.

Use cases

• learn how transformers and LLMs work from scratch
• understand KV caching and speculative decoding implementations
• study diffusion models and flow matching with minimal code
• learn reinforcement learning algorithms like PPO from scratch
• prepare to do deep learning research after learning basics
• understand tensor parallelism and GPU communication
• implement attention variants like linear attention myself

When to choose

• you want annotated, from-scratch implementations to learn deep learning deeply
• you're moving from beginner LLM tutorials toward research-level understanding
• you want single-GPU runnable reference code for modern techniques
• you prefer reading and hacking on minimal code over heavy frameworks

When to avoid

• you need production-ready, optimized model implementations
• you want a maintained library or framework to build applications on
• you need multi-node distributed training support
• you're looking for a plug-and-play model zoo

Facets

learning-resource · maturity active

machine-learning deep-learning llm-training reinforcement-learning llm-inference stable-diffusion gpu-computing deep-learning large-language-models machine-learning education tutorials python cross-platform educational from-scratch-implementations nanogpt annotated-code transformers diffusion-models research-education gpu

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