Introduction

Practical tutorials for developers building on Clore.ai's decentralized GPU marketplace.

What's Inside

This cookbook contains 40+ practical tutorials with real, working code examples. No fluff — just actionable recipes for:

• 🚀 Getting Started — Rent your first GPU in 5 minutes

• 🧠 Machine Learning — Train models, run distributed workloads

• ⚡ Inference & Deployment — Serve models at scale

• 📊 Data Processing — GPU-accelerated pipelines

• 🔧 DevOps & Automation — CI/CD, schedulers, monitoring

• 🎯 Advanced Use Cases — Bots, dashboards, multi-cloud

Quick Start

import requests

API_KEY = "YOUR_API_KEY"
headers = {"auth": API_KEY}

# Find available RTX 4090 servers
response = requests.get("https://api.clore.ai/v1/marketplace", headers=headers)
servers = response.json()["servers"]

available = [s for s in servers if "RTX 4090" in str(s.get("gpu_array", [])) and not s["rented"]]
print(f"Found {len(available)} available RTX 4090 servers")

Why Clore.ai?

Feature	Clore.ai	AWS/GCP
RTX 4090 (hourly)	~$0.20-0.40	N/A
A100 80GB (hourly)	~$1.50-2.50	~$4-6
Minimum commitment	1 minute	1 hour
Spot pricing	Yes (2.5% fee)	Yes (varies)
Setup time	< 2 minutes	5-15 minutes

Prerequisites

• Clore.ai account with API key

• Python 3.10+ (most examples)

• Basic Docker knowledge

• SSH client

Navigation

Use the sidebar to browse tutorials by category, or check SUMMARY.md for the full table of contents.

---

Built with 🔥 by the Clore.ai team