Moda community joins hands with vLLM and FastChat to provide Chinese developers with more convenient and efficient large language model inference and deployment services. This move aims to lower the development threshold and accelerate the implementation of LLM applications. As the inference engine of FastChat, vLLM significantly improves the throughput of model inference, while FastChat is an open platform covering the entire process of LLM-driven ChatBot training, service and evaluation. vLLM, jointly developed by researchers from Berkeley, Stanford and the University of California, San Diego, allows developers to quickly load magic models for reasoning, greatly simplifying the development process and injecting new vitality into the development of China's AI ecosystem.
Recently, the Moda community has cooperated with vLLM and FastChat to jointly provide Chinese developers with faster and more efficient LLM inference and deployment services. Developers can use vLLM as the inference engine in FastChat to provide high-throughput model inference. FastChat is an open platform for training, serving, and evaluating LLM-based ChatBots. vLLM is an LLM service system developed by researchers from the University of California, Berkeley, Stanford University, and the University of California, San Diego. Through FastChat and vLLM, developers can quickly load Moda's model for inference.
This cooperation integrates the advantages of multiple excellent platforms and provides developers with a complete and efficient set of LLM solutions. It is expected to promote technological development and application innovation in China's AI field and contribute to building a more prosperous AI ecosystem. In the future, we look forward to seeing more similar cooperation to jointly promote the progress and development of artificial intelligence technology.