Open Source Model

Open-source large language models (LLMs) aim to democratize access to powerful AI by providing freely available model weights, code, and sometimes even training data. Current research focuses on improving the performance and safety of these models, including developing novel training techniques, exploring efficient model compression methods like pruning and merging, and establishing robust benchmarks for evaluating trustworthiness, bias, and safety. This open approach fosters collaboration, accelerates innovation, and addresses concerns about proprietary model limitations, particularly regarding data privacy and accessibility for researchers and developers in various fields.