LLaMA 2: how to use Meta’s extremely powerful open-source chatbot now

Meta launched LLaMA 2, an extremely powerful open AI language model that challenges its competitors. It encourages researchers to build and improve AI. Different methods for accessing it are available, here they are.

Facebook’s parent company, Meta, made a splash in the artificial intelligence (AI) industry this week with the launch of LLaMA 2, a large-scale language model (LLM) open-source to challenge the restrictive practices of its major technological competitors.

Unlike AI systems launched by Google, OpenAI and others (like Apple with Apple GPT?), which are tightly guarded in proprietary models, Meta publishes LLaMA 2 code and data for free to enable researchers around the world to build and improve technology.

How does LLaMA 2 work?

Depending on the model you select, LLaMA 2 comes in three sizes: 7 billion, 13 billion, and 70 billion parameters. In comparison, OpenAI’s GPT-3.5 series includes up to 175 billion parameters, and Google’s Bard (based on LaMDA) has 137 billion.

The quantity of GPT-4 parameters was not disclosed by OpenAI in their published research. The number of parameters in a model is usually related to its performance and accuracy, but larger models require more computing resources and data for training.

The training method used for LLaMA 2 is also remarkable and different from popular alternatives. The tool is trained using Human Feedback Reinforcement Learning (HRLS), learning from the preferences and assessments of human AI trainers. In contrast, ChatGPT uses supervised fine tuning, learning from labeled data provided by human annotators.

How to use LLaMA 2?

Thanks to its open-source nature, several methods exist to enjoy LLaMA 2. Here are some of the easiest tips to access it and start experimenting with LLaMA 2 right now.

1. Interact with the chatbot demo

The simplest method to utilize LLaMA 2 is to go to llama2.ai, where Andreessen Horowitz is hosting a chatbot model demonstration.You can ask the template questions on any topic that interests you, or request creative content using specific prompts.

You can also change the chat mode between balanced, creative and precise according to your preferences. This is the best way to start and test this new model.

2. Download LLaMA Code 2

You may download LLaMA 2 straight from Hugging Face, a well-known portal for exchanging AI models, if you wish to run it on your own computer or modify the code.You will need a Hugging Face account and the necessary libraries and dependencies to execute the code.

3. Access via Microsoft Azure

Another option to access LLaMA 2 is through Microsoft Azure, a cloud computing service that offers different AI solutions. In the AI Azure Model Catalog, where you can explore, install, and manage AI models, you can discover LLaMA 2. You will need an Azure account and subscription to use this service. This method is recommended for more advanced users.

4. Access via Amazon SageMaker JumpStart

You can also experiment and deploy LLaMA 2 via Amazon SageMaker JumpStart, a popular hub of algorithms, models and solutions. SageMaker JumpStart simplifies the process of building, training and deploying machine learning (ML) models in just a few clicks. You will need an Amazon Web Services account and subscription to use this service. Caution, as this is another recommended method for more advanced users and programmers.

5. Try a variation on llama.perplexity.ai

Perplexity.ai is a web crawler that uses AI to generate general responses to your queries, then offers a series of links to websites. Llama.perplexity.ai combines the power of LLaMA 2 and Perplexity.ai to provide you with general answers and relevant links to your queries by using the new template to feed its answers.