An Overview of Meta’s Llama 2 Model: What’s New? An Overview of Meta’s Llama 2 Model: What’s New?
Over the course of the last few months, Meta’s Llama 2 has been making its rounds around the data science community... An Overview of Meta’s Llama 2 Model: What’s New?

Over the course of the last few months, Meta’s Llama 2 has been making its rounds around the data science community and so far has proven why it has become a big deal. Not only has it pushed the envelope when it comes to LLMs, but the open-source nature promises to help researchers push the boundaries of AI as the technology continues its rapid advance into the public imagination. 

So let’s take a look at a few key reasons Llama 2 is making waves.  

General Overview

Text Generation: Though for many writers this part makes them nervous, it’s undeniable that Llama 2 excels in generating text. But what’s interesting is that the model is quite diverse in its text generation skillset. Whether you need blog posts, articles, or even entire books, it can craft coherent and engaging content. This also includes creative pieces, such as poems, scripts, and even code snippets.

Translation: Language barriers are still an important issue that often has to be addressed for both business and personal reasons. This is why the market for language learning tools is still expected to explode by over 20% CAGR through the next ten years. But if Llama 2 can prove itself successful and able to integrate into general use by the public, it could change the ease with which people communicate. 

According to Meta, the model can effortlessly translate text from one language to another, making it a valuable tool for multilingual communication.

Code Generation: Llama 2’s abilities also extend to coding. The model is also able to generate code in various programming languages. But don’t expect it to put programmers out of work. The pain purpose of this would be to help programmers automate their tasks and accelerate development. This would allow programmers more time to imagine how to improve existing could or push barriers. 

Beyond that, it can produce imaginative code for artistic and musical endeavors, inspiring creativity.

Question Answering: One thing that is striking about Llama 2 is how knowledgeable and conversationalist the model has become. Though the nature of chatbots sees them interacting with humans quite well, Meta has pushed it hard with Llama 2 as they attempt to bridge communication barriers between man and machine. For example, a user can ask questions on a wide range of topics, and it responds informatively. 

But it doesn’t stop there—Llama 2 can also craft creative responses, weaving jokes and stories into its answers. Which adds a layer of naturalness to how it communicates to human users.

Improvements Over the Original

We’ve talked about some remarkable things Llama 2 has been able to do, let’s now focus on how it has been able to improve since its original iteration. 

Text Complexity: Llama 2 can generate longer and more complex text, making it suitable for a broader range of applications. Whether you need in-depth technical content or detailed explanations, it has you covered.

Question Understanding: This latest iteration has improved its question-answering capabilities. It’s better at grasping the nuances of queries, resulting in more precise and context-aware responses.

Creativity: Llama 2 takes creativity to the next level. If you require content that’s not just informative but also imaginative, it can conjure up content that engages and entertains your audience.

Who can use it?

Though Llama 2 is an open-source model, currently to be able to use it yourself, a request must be made directly to Meta via the following link. It’s available for both commercial and private use and Meta is betting that by being this open, it would help the Llama 2 model develop further as competitors such as Google and OpenAI have gone the opposite direction with their own LLMs’s code and kept them under lock and key. 


Now even though Llama 2 is quite impressive, there’s still a lot going on in the world of large language models. And if you want to keep up, the best way to do so is by meeting fellow professionals in person at events such as ODSC West. At West, you’ll not only meet and mingle with fellow data pros but also enjoy world-class keynotes, such as Meta’s own Thomas Scialom, PhD, in his session “Large Language Models: Past, Present and Future.”

So come, connect, communicate, and leave with greater knowledge. Get your pass today.



ODSC gathers the attendees, presenters, and companies that are shaping the present and future of data science and AI. ODSC hosts one of the largest gatherings of professional data scientists with major conferences in USA, Europe, and Asia.