Skill · em Dados, IA e pesquisa
nanogpt
Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).
Procedência
- Origem: davila7/claude-code-templates
- Caminho:
cli-tool/components/skills/ai-research/model-architecture-nanogpt - Versão fixada:
57f899e5394bb8ca166f38eacae8f0853cbfe033 - Licença: MIT
- Espelhado em 25/09/2026
- nenhum download no Claude Code Templates (lido em 25/09/2026)
Antes de instalar
4 arquivos · 42,2 KB · só texto, nenhum script
Instalar na sua CLI
O comando baixa a versão fixada (commit 57f899e) direto da origem, para a pasta que a CLI lê. Precisa de curl (macOS e Linux); no Windows não há comando, porque o Rook Labs é para macOS.
Claude Code
Neste projeto: instala em .claude/skills/nanogpt/.
d=".claude/skills/nanogpt" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/model-architecture-nanogpt" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/architecture.md" "$u/references/architecture.md" \ -o "$d/references/data.md" "$u/references/data.md" \ -o "$d/references/training.md" "$u/references/training.md"
Global: instala em ~/.claude/skills/nanogpt/.
d="$HOME/.claude/skills/nanogpt" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/model-architecture-nanogpt" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/architecture.md" "$u/references/architecture.md" \ -o "$d/references/data.md" "$u/references/data.md" \ -o "$d/references/training.md" "$u/references/training.md"
Codex
Neste projeto: instala em .agents/skills/nanogpt/.
d=".agents/skills/nanogpt" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/model-architecture-nanogpt" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/architecture.md" "$u/references/architecture.md" \ -o "$d/references/data.md" "$u/references/data.md" \ -o "$d/references/training.md" "$u/references/training.md"
Global: instala em ~/.agents/skills/nanogpt/.
d="$HOME/.agents/skills/nanogpt" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/model-architecture-nanogpt" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/architecture.md" "$u/references/architecture.md" \ -o "$d/references/data.md" "$u/references/data.md" \ -o "$d/references/training.md" "$u/references/training.md"
Antigravity
Neste projeto: instala em .agents/skills/nanogpt/.
d=".agents/skills/nanogpt" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/model-architecture-nanogpt" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/architecture.md" "$u/references/architecture.md" \ -o "$d/references/data.md" "$u/references/data.md" \ -o "$d/references/training.md" "$u/references/training.md"
Global: instala em ~/.gemini/antigravity-cli/skills/nanogpt/.
d="$HOME/.gemini/antigravity-cli/skills/nanogpt" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/model-architecture-nanogpt" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/architecture.md" "$u/references/architecture.md" \ -o "$d/references/data.md" "$u/references/data.md" \ -o "$d/references/training.md" "$u/references/training.md"
Peça ao Rook
Já usa o Rook Labs? Cole no chat do Rook: instale a skill https://rooklabs.sh/marketplace/cct.nanogpt
Prévia do SKILL.md
---
name: nanogpt
description: Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT architecture from scratch. Train on Shakespeare (CPU) or OpenWebText (multi-GPU).
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [Model Architecture, NanoGPT, GPT-2, Educational, Andrej Karpathy, Transformer, Minimalist, From Scratch, Training]
dependencies: [torch, transformers, datasets, tiktoken, wandb]
---
# nanoGPT - Minimalist GPT Training
## Quick start
nanoGPT is a simplified GPT implementation designed for learning and experimentation.
**Installation**:
```bash
pip install torch numpy transformers datasets tiktoken wandb tqdm
```
**Train on Shakespeare** (CPU-friendly):
```bash
# Prepare data
python data/shakespeare_char/prepare.py
# Train (5 minutes on CPU)
python train.py config/train_shakespeare_char.py
# Generate text
python sample.py --out_dir=out-shakespeare-char
```
**Output**:
```
ROMEO:
What say'st thou? Shall I speak, and be a man?
JULIET:
I am afeard, and yet I'll speak; for thou art
…