Introduction of LLama 3
Llama 3 is Meta’s latest family of open source large language models (LLM)which is claimed to be the most sophisticated model with significant progress in terms of performance and AI capabilities, representing the latest AI advancement.
Meta has released four versions of Llama 3 so far:
- Llama 3 8B
- Llama 3 8B-Instruct
- Llama 3 70B
- Llama 3 70B-Instruct
The 8B models have 8 billion parameters, while the two 70B models have 70 billion parameters. Both instruction tuned models are optimized for dialogue use cases and outperform many of the available open source chat models on common industry benchmarks, and fine-tuned to better follow human directions, so they’re more suited to use as a chatbot than the raw Llama models.
Llama 3 models accept input as a text only and generate output in text and code only.
It is an auto-regressive language model that uses an optimized transformer architecture. The instruction tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
Some of the data comes from publicly available sources like Common Crawl (an archive of billions of web pages), Wikipedia, and instruction datasets, as well as over 10M human-annotated examples. While some of it was also reportedly generated by AI (Neither the pretraining nor the fine-tuning datasets include Meta user data.)
Real-world Implementations of Llama 3
Utilizing Llama 3 goes beyond just ideas, as it’s actively used in real-world scenarios. Here are some key areas where Llama 3 is making a real difference.
- Content creation: Llama 3 can be used to generate different creative text formats, like poems, code, scripts, musical pieces, email, letters, etc.
- Chatbots: Llama 3 can be integrated into chatbots to make them more intelligent and informative. This can be used for customer service chatbots, virtual assistants, and more.
- Software development: Llama 3 can be used to generate code, translate languages, and write different kinds of creative text formats, which can be helpful for software developers.
- Websites/Mobile apps: Websites can use Llama 3 to create generative AI chatbots, generate content, answer user questions and personalize the user experience.
- Social media: Meta has integrated Llama 3 into its AI chat helper, which is used on Facebook, Instagram, and WhatsApp. This means that Llama 3 can be used to power AI chatbots on these platforms.
Why is Llama 3 better?
Most of the Large Language Models (LLMs) such as OpenAI’s GPT-3 and GPT 4, Google’s Gemini, and Claude are all proprietary and closed source. Researchers and businesses can use the official APIs to access them and even fine-tune versions of their models so they give tailored responses, but they are unable to delve deeply into or fully comprehend the inner workings of these models.
Llama 3 is openly accessible for almost anyone to use for research and commercial purposes.
The Llama 3 models have shown impressive performance across various benchmarks. The 70B model, for instance, outperforms other high-profile models like OpenAI’s GPT-3.5 and Google’s Gemini on tasks including coding, creative writing and summarization.
Here are some noteworthy features
- Huge Dataset: Llama 3 was trained on a dataset comprising 15 trillion tokens, which is about seven times the size of the dataset used for Llama 2. This extensive training has significantly contributed to the models’ improved performance and capabilities.
- Context length: All variants of Llama 3 support a context length of 8,000 tokens, allowing for more extended interactions and more complex input handling compared to many previous models. More tokens mean more content that includes both the input prompt from the users and the response from the model. Token roughly translates to a word or a subset of a word.
- Improved Inference: Llama 3 both 8B and 70B versions use a technique called Grouped-Query Attention (GQA) which boosts efficiency during information retrieval.
- Better Encoding: Llama 3 uses a tokenizer with a vocabulary of 128K tokens that encodes language much more efficiently, which leads to substantially improved model performance.
- Benchmark: Meta claims that in benchmark evaluations, Llama 3 8B surpassed other open-source AIs like Mistral 7B and Gemma 7B. Also, Llama 70B surpassed Gemini Pro 1.5, Mistral, and Claude 3.
Here is how Llama 3 8B and 70B stack up against other models working in “instruct” mode, where they have to do something like take tests or do math versus Google Gemma and Gemini Pro 1.5, Mistral, and Claude 3.
Here is how the pre-trained Llama 3 LLM stacked up against other pre-trained models for five different benchmarks :
How we can use Llama 3
With Llama 3, though, you can download the model, and as long as you have the technical chops, get it running on your computer or even dig into its code.
Llama 3 models are integrated into the Hugging Face ecosystem, making them readily available to developers. Developers and researchers rely on Hugging Face to download these models. This integration with Hugging Face includes tools like transformers and inference endpoints, facilitating easier adoption and application development.
Llama 3 is also available from model-as-a-service providers such as Perplexity Labs and Fireworks.ai, as well as cloud provider platforms such as Azure ML and Vertex AI.
Also, you can access the Llama 3 repository to access the code and use it.
Conclusion
In conclusion, Llama 3 emerges as a beacon of innovation and accessibility. Its open-source nature democratizes the field, inviting researchers, developers, and businesses alike to explore its vast potential. With impressive performance across various benchmarks and a dataset unparalleled in scale, Llama 3 stands poised to redefine the boundaries of what’s possible with language models.
Whether it’s generating creative text, enhancing chatbot interactions, aiding in software development, or personalizing user experiences, Llama 3 offers solutions to diverse challenges. Its integration into platforms like Hugging Face and cloud service providers further simplifies adoption, making its benefits accessible to all.
As we embark on this journey with Llama 3, let us embrace the opportunities it presents and push the boundaries of innovation together. With Llama 3 at our fingertips, the possibilities are limitless, and the future of AI brighter than ever before.