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Table Of Contents

Overview
Models
Llama 4 (New)
Llama 3.3
Llama 3.2
Llama 3.1
Llama Guard 3
Prompt Guard
Other models
Getting the Models
Meta
Hugging Face
Kaggle
1B/3B Partners
405B Partners
Running Llama
Linux
Windows
Mac
Cloud
How-To Guides
Fine-tuning
Quantization
Prompting
Validation
Vision Capabilities
Responsible Use
Integration Guides
LangChain
Llamalndex
Community Support
Resources
Overview
Models
Llama 4 (New)
Llama 3.3
Llama 3.2
Llama 3.1
Llama Guard 3
Prompt Guard
Other models
Getting the Models
Meta
Hugging Face
Kaggle
1B/3B Partners
405B Partners
Running Llama
Linux
Windows
Mac
Cloud
How-To Guides
Fine-tuning
Quantization
Prompting
Validation
Vision Capabilities
Responsible Use
Integration Guides
LangChain
Llamalndex
Community Support
Resources
Resources

Meta and Community Resources

A repository of Llama resources from videos to cookbooks.

If you have any feature requests, suggestions, bugs to report we encourage you to report the issue in the respective Github repository.

Note: Some of these resources refer to earlier versions of Llama. However, the concepts and ideas described are still relevant to the most recent version.

Meta Resources

RecipesFor our full list check out the Cookbook page.
Llama 4 Cookbook
A guide for building with Llama 4.
Learn more
Llama Stack Cookbook
A guide for building on Llama Stack.
Learn more
Llama on Hugging Face
The Llama Hugging Face repo.
Learn more
Llama 3 Cookbook
A guide for building with Llama 3
Learn more
How-to-guides
Fine-tuning
Full parameter fine-tuning is a method that fine-tunes all the parameters of all the layers of the pre-trained model.
Learn more
Quantization
Learn how quantization makes models more efficient for deployment on servers and edge devices.
Learn more
Prompting
Improve the performance of the language model by providing them with more context and information about the task in hand
Learn more
Validation
Learn different ways to measure and ultimately validate Llama
Learn more
Vision Capabilities
Interact with models in new ways.
Learn more
Developer Use Guide: AI Protections
Build Llama applications responsibly.
Learn more
Integration Guides
LangChain
Learn to build with this popular open source framework.
Learn more
LlamaIndex
Learn to build with this popular open source framework.
Learn more

Videos

Check out our video page to watch tutorials on Llama.

Watch now

Community Resources

Get Started with LlamaUse these cookbooks to get your journey with Llama started.
Building LLM applications for production
Start building apps with this guide
Learn more
Fine-tuningDiscover cookbook examples, data sets and more to help you jump start model fine-tuning.
Hugging Face PEFT
A repo for parameter-efficient fine-tuning (PEFT) on Llama.
Learn more
Efficient fine-tuning with LoRA
Databricks blog on efficient fine-tuning with LoRA.
Learn more
Weights & Biases training and fine-tuning large language models
A course on fine-tuning LLMs.
Learn more
End to end fine-tuning with torchtune
PyTorch native post-training library
Learn more
Fine-tuning comparison (Llama vs GPT)
The Pytorch Github library
Learn more
Fine-tuning comparison (Llama vs GPT)
The Pytorch Github library.
Learn more
How to fine-tune Llama with LoRA for Question Answering
NVIDIA deep learning blog on fine-tuning Llama.
Learn more
Performance & LatencyPapers and blogs to help optimize performance and latency.
Optimizing and testing latency for LLMs
An exploration of ways to optimize on latency
Learn more
Improving LLM interfaces
How continuous batching enables 23x throughput in LLM inference while reducing p50 latency.
Learn more
Improving performance of compressed LLMs with prompt engineering
A paper on improving accuracy-efficiency trade-off of LLM Inference.
Learn more
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