Large Language Models (LLMs)
Explore the world of Large Language Models, from understanding their architecture to practical applications and development resources.
📚 Major LLM Platforms 📚
🤖 OpenAI Models
Core Models
- 🔵 GPT-4 - Advanced Language Model
- 🔵 GPT-3.5 - Fast & Efficient
- 🔵 DALL-E 3 - Image Generation
Development Tools
- 🟡 API Reference - Integration Guide
- 🟡 Fine-tuning - Model Customization
- 🟡 Embeddings - Text Analysis
🤖 Google AI Models
Core Models
Development Tools
- 📗 Vertex AI - ML Platform
- 📗 Tutorials - Learning Resources
- 📗 Code Samples - Implementation
🤖 Meta AI Models
Core Models
Development Tools
- 🔍 AI Tools - Development Kit
- 🔍 Research - Technical Papers
- 🔍 Blog - Latest Updates
🔒 LLM Security
Security Practices
- 🔐 OWASP LLM Top 10 - Security Risks
- 🔐 NIST AI Framework - Risk Management
- 🔐 CISA Guidelines - AI Security
Best Practices
📚 Learning Resources
Courses & Tutorials
- 📜 DeepLearning.AI - LLM Courses
- 📜 Coursera - NLP Specialization
- 📜 Fast.ai - Practical Deep Learning
Research Papers
- 📜 arXiv - Latest Research
- 📜 Papers with Code - Implementations
- 📜 Google Scholar - Academic Papers
🛡️ Development Tools
Frameworks
- 🎯 Hugging Face - Model Hub
- 🎯 LangChain - LLM Framework
- 🎯 llama.cpp - Local Inference
Development Resources
🎯 Quick Tips
- Start with understanding transformer architecture
- Practice prompt engineering with different models
- Learn about tokenization and model limitations
- Understand ethical considerations and bias
- Experiment with fine-tuning on specific tasks