CLAUDE.md · diff
git:20260430.e647078 to git:20260603.cd0be25
4 added, 4 removed. Audit A to A.
# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## What This Repo Is
An Obsidian-based knowledge wiki covering LLM architecture — written in the style of Andrej Karpathy (intuition first, math second, no fluff). All content lives in `wiki/` as interlinked Markdown; source academic PDFs are in `raw/`.
## Environment Setup
- To activate the Conda environment and Azure Foundry integration before running Claude Code:
+ Copy `.env.example` to `.env` and provide your own credentials (Anthropic API key, or
+ Google Vertex AI project/region). See **How to Run Locally** in `README.md` for details.
+ Credentials must come from environment variables — never hardcode keys in tracked files.
```bash
- source activate_claude_w_Azure_API.sh
+ cp .env.example .env # then fill in your values
```
-
- This activates the `saqlain_vllm` Conda environment and sets `CLAUDE_CODE_USE_FOUNDRY=1` with Azure endpoints.
## Content Structure
- `wiki/Home.md` — top-level index with concept map and recommended reading order
- `wiki/000 Index.md` — full article list
- `wiki/*.md` — individual concept articles
- `raw/*.pdf` — source papers (Attention Is All You Need, Mamba, Mixtral, Switch Transformers, Nemotron-3)
## Architecture / Knowledge Graph
```
Transformer (2017)
│
├── O(n²) attention cost → Mamba: selective SSM, linear-time
├── Parameters tied to compute → Mixture-of-Experts: sparse routing
└── MoE communication bottlenecks → Nemotron-3 LatentMoE: route in latent space
Mamba + MoE + few attention layers = Nemotron-3 hybrid (best throughput-accuracy frontier, 2025)
```
Additional topics: KV Cache, GQA, Speculative Decoding, Multi-Token Prediction, State Space Models, RLVR, NVFP4, Hardware-Aware Scan, Load Balancing Loss.
## Writing Style for New Articles
Follow the pattern in existing articles: lead with intuition and motivation, use concrete analogies, introduce math only after the concept is clear. Use Obsidian `[[WikiLink]]` format for cross-references between articles.