training

Free hands-on labs for prompt injection and LLM security training, with real models, a context trace view of assembled prompts, and a multi-level Gauntlet challenge.

CodeTrain is a hands-on AI coding trainer that teaches developers on their own codebase by making them write each step themselves, with hints, test runs, and progress tracking.

A pure C implementation for training and running a tiny GPT, with build instructions, sample output, and performance notes for macOS, Linux, and Windows.

A tiny GPT implementation in pure Go, trained on Jules Verne books, with runnable code and notes that explain the model’s evolution and design choices.

Uno is a research repository for speeding up LLM inference with discrete diffusion and lossless multi-token decoding. The repo includes inference, training, and evaluation code, plus installation steps, checkpoints, and example workflows.

A hands-on workshop repository that walks developers through building a small GPT-style language model from scratch, including tokenization, transformer blocks, training, and text generation.

A Python CLI and research toolkit for simulating AI training math before model training. It estimates memory, training time, token budget, config risks, benchmark speed, and reliability, with optional native Rust and C backends.

A detailed technical write-up about training a 3.8B-parameter language model from scratch, including setup, throughput improvements, ablations, benchmarks, and cost/performance results.

Claudaholic is a daily swipe-based quiz product focused on Claude and agent workflows. It presents six fresh cards each day across judgment, orchestration, architecture, leverage, taste, and knowledge, aimed at helping users learn to read agent runs and make better decisions.