Transformers are a type of neural network architecture that processes entire input sequences in parallel using self-attention mechanisms, allowing them to capture long-range dependencies...
This blog post compares Transformers and RNNs, two popular deep-learning architectures for sequence-based tasks. Transformers excel at modeling long-range dependencies and parallel processing, making...
