Llama Models Guide

Llama Models

Meta's Llama family represents the leading open-source large language models.

Llama 3.x Series

Available Sizes

Key Features

• 128K context window - Handle long documents
• Multilingual - 8 languages supported
• Code generation - Strong programming ability
• Tool use - Native function calling

Running Llama Locally

With Ollama

# Pull model
ollama pull llama3.1:8b

# Run interactively
ollama run llama3.1:8b

# Use specific variant
ollama run llama3.1:70b

With llama.cpp

# Clone and build
git clone https://github.com/ggerganov/llama.cpp
cd llama.cpp && make

# Convert weights
python convert.py --outfile llama-3.1-8b.gguf

# Run
./main -m llama-3.1-8b.gguf -p "Hello, world"

API Usage

Python with Together AI

from openai import OpenAI

client = OpenAI(
    api_key="your-together-api-key",
    base_url="https://api.together.xyz/v1"
)

response = client.chat.completions.create(
    model="meta-llama/Llama-3.1-8B-Instruct-Turbo",
    messages=[
        {"role": "user", "content": "Explain quantum computing"}
    ]
)
print(response.choices[0].message.content)

With Groq (Fast Inference)

from groq import Groq

client = Groq(api_key="your-groq-api-key")

response = client.chat.completions.create(
    model="llama-3.1-70b-versatile",
    messages=[{"role": "user", "content": "Hello!"}]
)

Llama 3.2 Multimodal

# Vision model usage
from ollama import chat

response = chat(
    model='llama3.2-vision',
    messages=[{
        'role': 'user',
        'content': 'Describe this image',
        'images': ['./image.jpg']
    }]
)

Best Practices