| """ | |
| The most atomic way to train and run inference for a GPT in pure, dependency-free Python. | |
| This file is the complete algorithm. | |
| Everything else is just efficiency. | |
| @karpathy | |
| """ | |
| import os # os.path.exists | |
| import math # math.log, math.exp |
I learn Rust by reading The Rust Programming Language (aka. TRPL) book.
This is my mind map and collection of resources for learning Rust in early 2019.
I plan to continuously update this list if time allows in future. I will move this into its own GitHub repo or something more permanent when this grow.
Core workspace .md files are injected into the LLM system prompt on most requests, with some files loaded conditionally by context. Size still directly impacts token cost, so keep files focused and avoid duplication across files.
These three docs answer different questions:
| File | Primary question it answers | What belongs here | What should not go here |
|---|