What is Llama 3 Series (Meta AI)?

The Llama 3 Series is the next generation of open-source large language models (LLMs) developed by Meta AI. Building on the success of its predecessors, Llama 3 models are designed to be best-in-class, offering state-of-the-art performance across a wide range of industry benchmarks. They excel at tasks like nuanced conversation, code generation, logical reasoning, and following complex instructions. The series includes models of various sizes (e.g., 8B and 70B parameters) to cater to different computational needs, from on-device applications to large-scale cloud deployments.

Key Features

• State-of-the-Art Performance: Llama 3 models are highly competitive with top proprietary models in benchmarks for reasoning, coding, and creative writing.
• Multiple Model Sizes: Available in 8B and 70B parameter versions, allowing developers to choose the right balance of performance and resource requirements.
• Improved Pre-training: Trained on a massive, high-quality dataset over 15 trillion tokens, with advanced data-filtering pipelines to ensure robustness and knowledge breadth.
• Enhanced Safety: Includes built-in safety features and guardrails, developed through techniques like Llama Guard 2 and Code Shield, to promote responsible AI development.
• Generous Open-Source License: Released under the Meta Llama 3 Community License, allowing for broad commercial and research use.
• Optimized for Dialogue: The instruction-tuned models are specifically optimized for natural, back-and-forth conversations.

Use Cases

• Advanced Chatbots & Virtual Assistants: Powering sophisticated conversational agents that can handle complex user queries.
• Code Generation & Debugging: Assisting developers by writing, completing, and debugging code in various programming languages.
• Content Creation: Generating high-quality text for articles, marketing copy, emails, and creative stories.
• Summarization & Information Extraction: Condensing long documents into concise summaries and extracting key information from unstructured text.
• Research & Development: Serving as a powerful foundation for researchers exploring the frontiers of AI.

Getting Started

Here is a “Hello World” style example of how to run the Llama 3 8B Instruct model using the transformers library in Python.

First, ensure you have the necessary libraries installed: ```bash pip install transformers torch accelerate

Then, you can use the following Python code to generate text: ```python import transformers import torch

model_id = “meta-llama/Meta-Llama-3-8B-Instruct”

pipeline = transformers.pipeline( “text-generation”, model=model_id, model_kwargs={“torch_dtype”: torch.bfloat16}, device_map=”auto”, )

messages = [ {“role”: “system”, “content”: “You are a friendly chatbot who always responds in the style of a pirate.”}, {“role”: “user”, “content”: “Hello, who are you?”}, ]

prompt = pipeline.tokenizer.apply_chat_template( messages, tokenize=False, add_generation_prompt=True )

terminators = [ pipeline.tokenizer.eos_token_id, pipeline.tokenizer.convert_tokens_to_ids(“<|eot_id|>”) ]

outputs = pipeline( prompt, max_new_tokens=256, eos_token_id=terminators, do_sample=True, temperature=0.6, top_p=0.9, )

print(outputs[0][“generated_text”][len(prompt):])

Expected output might be:

Ahoy, matey! I be a friendly chatbot, sailin’ the digital seas. What treasures can I help ye find today?

Pricing

Llama 3 models are Free and Open Source under the Meta Llama 3 Community License. This allows for free use in research and commercial applications, though some restrictions apply, particularly for services with over 700 million monthly active users.