Llama
Llama (Large Language Model Meta AI) is a family of open-weight large language models released by Meta, ranging from 1B to 405B+ parameters. Starting in 2023, Meta has iterated through Llama 1, 2, 3, and 4, with each generation adding longer context windows, multimodal capabilities, and Mixture-of-Experts (MoE) architectures. Because the weights are publicly available, Llama models can be fine-tuned, deployed on-premises, or integrated into products without API gatekeeping.
In 2026, enterprises increasingly demand AI solutions that keep data on-premises for compliance and cost reasons, making open-weight models like Llama a critical alternative to closed-source APIs. AI engineers who can fine-tune, quantize, and deploy Llama models—using techniques like LoRA, QLoRA, and RAG—are in high demand across industries from healthcare to retail. Meta's continued investment in the Llama ecosystem means the model family is updated frequently, making it a durable foundational skill for any LLM practitioner.
🎓 Courses
Building with Llama 4
by Amit Sangani (Meta, Director of Partner Engineering)
The most current course covering Llama 4 Maverick and Scout, including MoE architecture, 1M–10M token context windows, multimodal image reasoning, and building agentic apps with Llama Stack API. Made in collaboration with Meta.
Introducing Multimodal Llama 3.2
by Amit Sangani (Meta)
Covers Llama 3.2's tool-calling, iPython role, and the Llama Stack API for building agentic workflows. A practical bridge between Llama 3 and 4 capabilities.
Hands-On LLaMA-3 Course: Build, Fine-tune, and Deploy LLMs
by 365 Data Science team
End-to-end practical course: run Llama in Google Colab, apply LoRA/QLoRA fine-tuning, build a RAG system, and deploy a real-time API. Good starting point for practitioners without prior LLM experience.
LLM Course (Hugging Face)
by Hugging Face team
Comprehensive open-source course covering LLM fundamentals, fine-tuning (including Llama-family models), and building reasoning models. Free and continuously updated with the latest Hugging Face tooling.
meta-llama Model Hub & Documentation
by Meta AI
Official Meta model cards and documentation for every Llama release. Contains usage examples, benchmarks, and fine-tuning guidance directly from Meta—essential reference material for any Llama practitioner.
📖 Books
Hands-On Large Language Models: Language Understanding and Generation
Jay Alammar, Maarten Grootendorst · 2024
Highly visual, practical guide to LLMs including Llama, covering Transformer internals, semantic search, fine-tuning with LoRA, and RAG pipelines. Authors are recognized experts (Cohere, Google DeepMind). Published O'Reilly September 2024.
Building LLM Powered Applications
Valentina Alto · 2024
Packt 2024 guide to embedding LLMs including open-weight models into real-world apps using LangChain. Covers fine-tuning Llama-family models for domain-specific use cases and production deployment patterns.
🛠️ Tutorials & Guides
Meta Llama Official Blog & Release Notes
Meta's own announcements for each Llama release provide authoritative architecture summaries, benchmark comparisons, and download instructions. The Llama 4 post covers MoE design, multimodal capabilities, and deployment recommendations.
LLaMA Course: 200+ Courses Aggregated
Curated directory of 200+ free and paid Llama courses across DataCamp, YouTube, LinkedIn Learning, and more. Useful for finding tutorials at any level—from beginner RAG demos to advanced quantization and GGUF deployment with Ollama.
Learning resources last updated: June 18, 2026