RWKV

RWKV is a cutting-edge neural network architecture that combines the strengths of recurrent neural networks (RNNs) with the performance of transformer-based large language models (LLMs). Unlike traditional RNNs, RWKV achieves transformer-level performance, making it highly efficient for various natural language processing tasks. One of its key advantages is its ability to be trained in parallel, similar to GPT models, enabling faster and more scalable training processes. RWKV offers a versatile solution for researchers and developers seeking to leverage the power of LLMs while maintaining the benefits of RNN architectures.