Transformer-based neural networks are extremely large. These networks have several nodes and layers. Every node inside a layer has connections to all nodes in the subsequent layer, each of that has a weight and also a bias. Weights and biases in addition to embeddings are known as design parameters. I https://leadingmachinelearningcom79887.blogsvirals.com/25831780/the-best-side-of-large-language-models