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In many generative AI applications, a large language model (LLM) like Amazon Nova is used to respond to a user query based on the models own knowledge or context that it is provided. Lulu Wong is an AI UXdesigner on the Amazon Artificial General Intelligence (AGI) team.
The Hugging Face containers host a large language model (LLM) from the Hugging Face Hub. They are designed for real-time, interactive, and low-latency workloads and provide auto scaling to manage load fluctuations. You can use other languages such as Spanish, French, or Portuguese, but the quality of the completions may degrade.
The article is written for product managers, UXdesigners and those data scientists and engineers who are at the beginning of their Text2SQL journey. To ensure a sufficient quantity of training examples, data augmentation can be used — for example, LLMs can be used to generate paraphrases for the same question. [3]
Not only are large language models (LLMs) capable of answering a users question based on the transcript of the file, they are also capable of identifying the timestamp (or timestamps) of the transcript during which the answer was discussed. Each citation can point to a different video, or to different timestamps within the same video.
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