Large Language Models: Part 2
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Large Language Models: Part 2
Last time, we explored the capabilities of neural networks in approximating functions and delved into how they could be applied to language modeling. This article will focus on the utilization of large language models, particularly transformers, to handle complex language tasks such as prediction and generation. We will discuss the architecture of transformers, the training process, their remarkable capabilities, and some of the challenges they face.
Large Language Models: Part 2
Large language models, neural networks, word embeddings, attention network, prediction network, transformer, GPT-3, training process, internet data, capabilities, challenges