Get ready to be blown away by the latest addition to the advanced large language models! Meta AI has just unveiled the Llama 2, a cutting-edge model that's set to shake up the game for builders and developers everywhere. Say goodbye to the limited options of language models and hello to a whole new level of power and flexibility. Want to know more? Keep reading! 

We'll dive into all the juicy details of this innovative model and what it can do for you.


  • Meta AI has released the Llama 2 language model, which is more advanced and efficient than its predecessor, Llama 1.
  • It was trained on publicly available online data worth a total of 2 trillion tokens across three different parameters sizes: 7 billion, 13 billion, and 70 billion.
  • It has two reward models developed by Meta AI using reinforcement learning with human feedback, one focusing on helpfulness and the other on safety.
  • Llama 2 language model has been proven more effective than ChatGPT-3.5 in a prompt comparison test.
  • If you are looking for an AI chatbot with more versatile language models than Llama 2, ZenoChat is designed for you.
  • ZenoChat is a customizable conversational AI developed by TextCortex that uses a different set of language models to provide human-like conversation experience.

Brief Overview of Llama 2

The Llama 2 language model was released by Meta AI, a partnership with Microsoft, on July 18, 2023. The Llama 2 language model has been developed to be 40% more efficient and advanced than its predecessor, Llama 1. Meta AI trained and released Llama 2 in three model sizes: 7 billion, 13 billion, and 70 billion.

A brief overview of LLaMa 2

Pretrained Data

Llama 2, an updated version of Llama 1, trained on a mix of publicly available online data, 40% more than its predecessor. The Llama 2 language model has been trained with data worth 2 trillion tokens in total. It should be noted that each 4K token equals approximately 3500 words.

Another news is that the Llama 2 language model is not trained with data from Meta products and services. The developer team avoided using data containing personal information while building the Llama 2 language model. Our knowledge on this subject is limited, as Meta AI does not specify the source of the data it uses for the train.


The Llama 2 language model has been released in three different parameter sizes: 7 billion, 13 billion, and 70 billion. In addition, the Llama 2 language model has also an unreleased version with 34 billion parameters size.

Reinforcement Learning with Human Feedback (RLHF)

When developing the Llama 2 large language model, Meta AI used a technology called Reinforcement Learning with Human Feedback (RLFH) to fine-tune it. This process generates output based on human preferences and creates a pattern of which of the model's outputs is preferred by humans. Although the method is simple, it is effective in improving output quality.

Llama 2 Chatbot

If you're curious about how LLaMa 2 chat performs, here is the place where you can try it out. As it's the smallest 7B model of LLaMa 2, you'll undoubtedly notice the divergences between your experience and ChatGPT. Nevertheless, it's a fully open-source and free model. This is a significant contribution to the industry.

llama 2 chatbot

Two Separate Reward Models

Meta AI has developed two different reward models using reinforcement learning with human feedback while training the Llama 2 language model. One of these models focuses on helpfulness. Therefore, the Llama 2 language model has been enabled to generate better outputs and provide more valuable results. The second reward model focused on safety. As a result, the Llama 2 language model has been programmed to avoid generating responses that contain harmful and unethical terms.

How are Reward Models trained?

Reward models are determined by choosing the one that is most suitable for people's preferences among the results. To visualize it, if you have trained a dog at some point in your life, you can better understand the training format of the reward models. We can say that the Llama 2 language model is also trained with the same technique.

How do Reward Models Work?

When you input the Llama 2 chatbot, the model generates several different outputs. Each output is scored as safety and helpfulness by reward models. The generated text with the highest score is output to the user.

what's new with llama 2?

Is Llama 2 better than ChatGPT?

Llama 2 language model is better if you are using ChatGPT with the default GPT-3.5 model. As a result of the Meta AI's 4000 prompt comparison test, the Llama 2 language model has proven to be more effective than the ChatGPT-0301 model.

llama2 vs chatgpt

However, we would like to point out that the ChatGPT-0301 chatbot works with the GPT-3.5 language model. In other words, the Llama 2 language model is not better than GPT-4 because GPT-4 is several times more effective than its predecessor GPT-3.5. According to this benchmark, the Llama 2 language model can't beat GPT-4. If you are using ChatGPT with the GPT-4 language model, it is still more effective and efficient than Llama 2.

llama 2 vs gpt4

What if we told you that there is a free way to use the GPT-4 language model, which is better than Llama-2? The answer is ZenoChat. ZenoChat by TextCortex gives 20 free creations for free plan users to openly experience large language models such as GPT-4 and Sophos 2.

Better Alternative: ZenoChat

Considering that the GPT-4 language model is more effective than Llama 2, ZenoChat using not only GPT-4, but also Sophos-2 - a language model of its own, is the best alternative. ZenoChat is a conversational AI of your dreams developed by TextCortex. It is available as a web application and browser extension. The ZenoChat browser extension is integrated with 10.000+ websites and apps including Google Docs, Gmail, Outlook, Notion Facebook and many more.

Capabilities of ZenoChat

ZenoChat is designed to provide users with a human-like conversation experience with advanced language models. You can chat with it or give it commands to complete your tasks.

ZenoChat includes a web search option that allows you to access up-to-date information from Google. With the web search feature, you can activate ZenoChat to utilize the internet, Wikipedia, Scholar, news, YouTube, Reddit, and Twitter when producing results.

ZenoChat is designed to generate perfect output in 25+ languages. If you work in a multilingual business or want to access resources in different languages, ZenoChat is the way to go.

You don't have to type to use ZenoChat, thanks to its speech-to-text feature, you can use voice commands and take your conversational AI experience to the next level.

Customize ZenoChat

ZenoChat is a conversational AI where you can customize both its database and response style as you wish. Thanks to the "Knowledge Bases" feature of TextCortex, you can upload your documents and connect resources such as Google Drive and Notion. Thus, you can make ZenoChat use the resources you specify while generating output. Moreover, you can chat with your documents or translate them into different languages with a single click.

ZenoChat comes with 12 different personas, customized to help complete various tasks. If these personas are not enough for you, you can build your own digital AI with the "Individual Personas" feature. The good news is you don't need coding skills or technical experience to add personas to ZenoChat.

How to Access ZenoChat?

All you must do to access ZenoChat is to create your free TextCortex account. You can then access ZenoChat using our web application or browser extension. You can continue to use ZenoChat without changing tabs, as our browser extension integrates with 4000+ websites and apps.