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Mercury allows training custom GPT models to chat with any document or website.

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Mercury is a platform designed to create specialized GPT models that can interact with content from documents or websites. It does this through a series of steps that begin with either uploading documents directly into the system or using its web crawling capabilities to gather data from specified websites. Once the data is collected, Mercury utilizes this information to train a custom GPT model. This training process allows the model to understand and interact with the content, making it possible to engage with the uploaded or crawled data through a conversational interface.

Users can input queries related to the content, and the trained model responds in a manner akin to a chatbot but tailored specifically to the content it has been trained on. This means that if a user uploads technical manuals, legal documents, or any other specific material, Mercury trains a model to understand and interact with this material specifically. Similarly, if the system crawls a website, it can extract relevant information, which it then uses to train a model capable of engaging with queries related to that website’s content.

This approach allows for highly customized interactions, enabling users to “chat” with a document or website through the trained model. It is particularly useful for extracting information, answering questions, or simply navigating through the content of the documents or websites in a more interactive and conversational manner. Mercury’s capability to support both file uploads and web page crawling for data extraction followed by training on this data, positions it as a versatile tool for creating custom GPT models designed for specific content interaction.

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