I implemented it myself in my bot, defining what is acceptable based on how people chat and what they might mean when they say certain things. I never actually used that feature for Cohere Command R. The dataset I am using is just the chat, the user chat, and it is not that big. It is just a few months, and I always clear the chats after a few months. So it is just normal content, nothing extraordinary; I do not think it can be quantified as big data.
Large Language Models are AI systems designed to understand and generate human language. They process and produce text, enabling applications like chatbots and content generation, transforming human-computer interaction. These advanced AI models use substantial datasets to learn language patterns, providing functionalities in natural language processing, translation, and conversational interfaces. Through machine learning techniques, they generate coherent and contextually relevant text...
I implemented it myself in my bot, defining what is acceptable based on how people chat and what they might mean when they say certain things. I never actually used that feature for Cohere Command R. The dataset I am using is just the chat, the user chat, and it is not that big. It is just a few months, and I always clear the chats after a few months. So it is just normal content, nothing extraordinary; I do not think it can be quantified as big data.
My main use case for Cohere Command R is for a GenAI application. For the RAG project, we are using Cohere Command R for the retrieval process.