fastai/lm-hackers resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1869 stars · 310 forks observed · 2026-08-28

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

A Jupyter notebook and accompanying video guide from fast.ai explaining how language models work, including tokenization, base models, instruction tuning, and RLHF. It also includes configuration files for fine-tuning models with axolotl.

Use cases

• learn how large language models work from scratch
• understand tokenization and how LLMs process text
• get started with fine-tuning open source LLMs using axolotl
• learn to build applications on top of OpenAI language model APIs
• understand instruction tuning and RLHF concepts
• follow a hands-on hacker-style introduction to language models

When to choose

• you want a fast, practical video-plus-notebook introduction to LLMs
• you are a developer learning to use and fine-tune language models
• you want example axolotl configs for fine-tuning

When to avoid

• you need production-ready LLM inference or training code
• you want a comprehensive structured course rather than a single notebook
• you need up-to-date coverage of the newest LLM techniques

Facets

learning-resource · maturity maintenance

llm-inference llm-training prompt-engineering rag large-language-models tutorials artificial-intelligence education python cli jupyter-notebook tutorial fine-tuning axolotl openai video-course

Member repositories

For agents

markdown · JSON · MCP: product_card(name="fastai/lm-hackers")