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Tutorial Notebooks

Complete tutorial series for llcuda v2.2.0 on Kaggle dual T4 - 13 comprehensive tutorials from beginner to advanced.

Recommended Setup

  • Kaggle notebook with 2× Tesla T4 (30GB VRAM)
  • CUDA 12 environment
  • Use the Kaggle Setup Guide before starting

Core Tutorials (1-10)

# Notebook Open in Kaggle Description Time
01 Quick Start Kaggle 5-minute introduction 5 min
02 Server Setup Kaggle Server configuration 15 min
03 Multi-GPU Kaggle Dual T4 tensor-split 20 min
04 GGUF Quantization Kaggle K-quants, I-quants 20 min
05 Unsloth Integration Kaggle Fine-tune → Deploy 30 min
06 Split-GPU + Graphistry Kaggle LLM + Visualization 30 min
07 Knowledge Graph Extraction Kaggle LLM-driven entity & relation graphs 30 min
08 Document Network Analysis Kaggle GPU graph analytics for documents 35 min
09 Large Models (13B+) Kaggle Large models on dual T4 30 min
10 Complete Workflow Kaggle End-to-end 45 min

Visualization Trilogy (11-13)

# Notebook Open in Kaggle Description Time
11 GGUF Neural Network Visualization Kaggle Complete model architecture as interactive graphs 60 min
12 GGUF Attention Mechanism Explorer Kaggle Q‑K‑V attention analysis 20 min
13 GGUF Token Embedding Visualizer Kaggle 3D embedding space exploration 15 min

Learning Paths

Beginner (1 hour)

Start here if you're new to llcuda: 

01 → 02 → 03
Quick Start → Server Setup → Multi-GPU

Intermediate (3 hours)

Full fundamentals with deployment: 

01 → 02 → 03 → 04 → 05 → 06 → 07 → 10
All basics through complete workflow

Advanced (2 hours)

Multi-GPU focus for large models: 

01 → 03 → 08 → 09
Quick Start → Multi-GPU → Document Network Analysis → Large Models

Complete architecture analysis with Graphistry: 

01 → 03 → 04 → 06 → 11 → 12 → 13
Quick Start → Multi-GPU → GGUF → Split-GPU → Visualization Trilogy

Complete Master (6 hours)

Everything from basics to advanced visualization: 

01 → 02 → 03 → 04 → 05 → 06 → 07 → 08 → 09 → 10 → 11 → 12 → 13
All tutorials in order