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Showing posts with the label LLaMA 2

LLaMA 2 and its Symbolic Regression Explanation

On July 17, a new family of AI models, LLaMA 2 was announced by Meta. LLaMA 2 is trained on a mix of publicly available data. According to Meta LLaMA 2 performs significantly better than the previous generation of LLaMA models. Two flavors of the model: LLaMA 2 and LLaMA 2-Chat, a model fine tuned for two-way conversations, were released. Each flavor further has three versions with the parameters ranging from 7 billions to 70 billions. Meta is also freely releasing the code and data behind the model for  researchers to build upon and improve the technology. There are several ways to access LLaMA 2 for development work; you can download it from HuggingFace or access it via Microsoft Azure or Amazon SageMaker . For those interested in interacting with the LLaMA 2-Chat version, you can do so by visiting , a chatbot model demo hosted by the venture capitalist Andreessen Horowitz. This is the route I took to interact with LLaMA 2-Chat. Since I was reading an excellent paper on