# Llama Models — Official Meta Model Utilities and Definitions

> The official Meta repository containing model definitions, tokenizer utilities, and reference implementations for the Llama family of large language models including Llama 2 and Llama 3.

## Install

Save as a script file and run:

# Llama Models — Official Meta Model Utilities and Definitions

## Quick Use
```bash
pip install llama-models
```
```python
from llama_models.llama3.api import Llama3Tokenizer

tokenizer = Llama3Tokenizer("/path/to/tokenizer.model")
tokens = tokenizer.encode("Hello, world!", bos=True, eos=False)
print(tokens)
```

## Introduction
Llama Models is Meta's official repository providing model architecture definitions, tokenizer implementations, and utility code for the Llama family of open-weight language models. It serves as the canonical reference for anyone building on top of Llama 2, Llama 3, or subsequent releases, providing the exact model specifications and supporting code.

## What Llama Models Does
- Provides official model architecture definitions for all Llama variants and sizes
- Includes tokenizer implementations with the correct vocabulary and special tokens
- Defines model configuration parameters (dimensions, layers, heads) for each release
- Offers prompt formatting utilities for chat, instruction, and tool-use templates
- Documents the safety system prompt and content filtering approach

## Architecture Overview
The repository contains Python dataclass definitions for model hyperparameters, a reference transformer implementation, and the SentencePiece/tiktoken-based tokenizer. Llama 3 uses a standard decoder-only transformer with grouped-query attention (GQA), RoPE positional embeddings, SwiGLU activations, and RMSNorm. The configs specify exact dimensions for 8B, 70B, and 405B parameter variants.

## Self-Hosting & Configuration
- Install via pip to access model definitions and tokenizer utilities programmatically
- Download model weights separately from Meta's official distribution portal after license acceptance
- Use the provided configs to initialize models in PyTorch, Hugging Face, or custom frameworks
- Reference the chat template formatting for correct multi-turn conversation structure
- Integrate the tokenizer with inference servers like vLLM, TGI, or llama.cpp

## Key Features
- Canonical source of truth for Llama model specifications and configurations
- Chat template definitions ensuring correct prompt formatting across deployments
- Support for tool calling and structured output format specifications
- Backward-compatible utilities covering Llama 2 through Llama 3 model families
- Clear documentation of model capabilities, limitations, and intended use cases

## Comparison with Similar Tools
- **Hugging Face Transformers** — provides converted model weights and inference; llama-models is the authoritative source for architecture specs
- **llama.cpp** — C++ inference engine; llama-models provides the Python reference implementation
- **LitGPT** — training framework supporting Llama; llama-models is Meta's official definition only
- **Ollama** — end-user LLM runner; llama-models targets developers building on the architecture
- **Llama Stack** — Meta's full application framework; llama-models focuses on model definitions

## FAQ
**Q: Do I need this package to use Llama models?**
A: Not necessarily. Most users access Llama via Hugging Face or Ollama. This package is for developers who need the canonical model definitions or tokenizer directly.

**Q: Where do I get the actual model weights?**
A: Download weights from Meta's official portal (llama.meta.com) or from Hugging Face Hub after accepting the license agreement.

**Q: What is the license for Llama models?**
A: Llama 3 uses the Meta Llama 3 Community License, which allows commercial use with some restrictions for very large deployments.

**Q: Does this support fine-tuning?**
A: The repository provides model definitions. For fine-tuning, use frameworks like torchtune, Axolotl, or LLaMA-Factory with the architecture from this package.

## Sources
- https://github.com/meta-llama/llama-models
- https://llama.meta.com

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Source: https://tokrepo.com/en/workflows/asset-bb0362a5
Author: Script Depot