Faster Text Generation with Self-Speculative Decoding

The article introduces Self-Speculative Decoding (SSD), a new decoding method designed to accelerate text generation in language models. SSD leverages a dual-pass mechanism where a lightweight model generates speculative tokens that are later verified by a more powerful model, significantly reducing overall generation time while maintaining quality. This approach is particularly relevant for practitioners looking to optimize inference speed in large language models without compromising output fidelity.