Researchers have developed a new method for training large language models that achieves native speed, meaning it can process and generate text at the same rate as other tasks on a computer. This is made possible by using a technique called vLLM (variable-length long short-term memory), which allows transformers to model longer input sequences without sacrificing performance. The new backend is designed for use with Hugging Face's Transformers library, a widely-used toolkit for natural language processing. --- Why it matters: This matters because it enables faster and more efficient training of large language models, which are crucial for many applications in AI research and industry. This breakthrough could lead to improved performance and reduced computational costs for tasks like text generation and question-answering. Source: https://huggingface.co/blog/native-speed-vllm-transformers-backend